Employment opportunities, postdoctoral positions, summer jobs

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Postdoctoral Researcher, University of Memphis (USA)

  • Employer: Institute for Intelligent Systems, University of Memphis, USA
  • Specialty: Cognitive Science with an emphasis on language, learning, and/or AI
  • Location: Memphis, TN USA
  • Deadline: open until filled
  • Contact: Andrew Olney
  • Date posted: March 5th 2020
  • Start Date: May 1st 2020

The Institute for Intelligent Systems at The University of Memphis invites applications for a postdoctoral researcher. The 12-month position will start in May 2020 pending the availability of funds. Candidates must have a Ph.D. in hand by May 2020 and must have a compelling record of research success and potential.

The successful candidate will complement interdisciplinary research at the IIS in one or more of the following focus areas: learning, language, and artificial intelligence. Candidates are encouraged to work on their own research agenda but may join existing projects. Mentoring will be provided based on research focus. Candidates from minority and underrepresented groups are highly encouraged to apply. Salary is competitive and commensurate with qualifications and experience.

Please submit a letter detailing current research interests, a curriculum vitae, three representative publications, and email addresses for three professional references on-line at https://workforum.memphis.edu. For all other inquiries please contact Andrew Olney, aolney@memphis.edu. Review of applications will begin on March 1, 2020.

A background check will be required for employment. The University of Memphis is an Equal Opportunity/Equal Access/Affirmative Action employer committed to achieving a diverse workforce.

Two Research Fellows in Natural Language Processing, Artificial Intelligence Research Centre, Japan

  • Employer: Artificial Intelligence Research Centre, Japan and the National Centre for Text Mining, UK
  • Specialty: Natural Language Processing, Information Extraction, Knowledge Discovery
  • Location: Tokyo, Japan
  • Deadline: 31st March 2020
  • Contact: Sophia Ananiadou
  • Date posted: March 4th 2020
  • Start Date: ASAP

The Artificial Intelligence Research Centre, Japan and the National Centre for Text Mining (UK) invite applications for two Research Fellows in Natural Language Processing. This is an exciting opportunity for two ambitious researchers to work on a major interdisciplinary project on Cancer, funded by the Japan Agency for Medical Research and Development. The posts aim to promote novel research into information extraction and knowledge discovery for immunotherapy for cancer mechanisms. The two fellows will work together and will also collaborate with NLP researchers both in Japan and in the UK, as well as with data scientists and medical practitioners in Japan.

Although the posts will be located in AIRC, Japan (https://www.airc.aist.go.jp/en/intro/), the NLP research will be carried out in collaboration with the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk), Department of Computer Science at The University of Manchester. The successful candidates will benefit from the vibrant research environments of both AIRC and NaCTeM.

Essential skills: candidates should have a PhD in Computer Science with an emphasis on Natural Language Processing/Machine Learning. They should have excellent knowledge of neural network architectures for NLP, information extraction (relation and event extraction) at scale, unsupervised learning or distant learning. Good programming skills (Perl, Python or other scripting languages) are highly desirable. Candidates should have a proven publication track record in high quality venues (e.g. ACL, EMNLP, AAAI, NAACL, etc.). Fluency in English is a must. They should have good written skills in English, be able to communicate with the partners of the consortium and work independently to meet deadlines.

Applicants should send a detailed CV, including a list of publications, a covering letter indicating their expertise for this project and the names of three referees, to Professor Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk).

Interviews will be held during the first week of April 2020, with the aim of starting the project as soon as possible.

Salary: ~6M yen to 9M yen per year (£43K to £65K), depending on experience.

Duration of posts: 3 years.

Postdoc in Computational Neurolinguistics, University of Georgia (USA)

  • Employer: Department of Linguistics, University of Georgia, Athens GA USA
  • Specialty: Natural Language Processing, Human Neuroimaging, Cognitive Science
  • Location: Athens, Georgia USA
  • Deadline: open until filled
  • Contact: John Hale
  • Date posted: March 2nd 2020
  • Start Date: August 1st 2020

Duties include using tools and techniques from computational linguistics to analyze neural signals across languages. The successful candidate will work closely with partners in Michigan, at Neurospin, INRIA and the MPI. Apply at https://www.ugajobsearch.com/postings/83958

Postdoctoral Researcher in NLP for healthcare, Vrije Universiteit Brussel (VUB) - imec, Belgium

  • Employer: Electronics and Informatics (ETRO), at Vrije Universiteit Brussel (VUB) - imec, Belgium
  • Title: Postdoctoral Researcher in NLP for healthcare
  • Specialty: NLP, Machine Learning
  • Location: Brussels
  • Deadline: March 29, 2020
  • Date posted: February 25, 2020
  • Contact: ndeligia@etrovub.be

The department of Electronics and Informatics (ETRO) at Vrije Universiteit Brussel (VUB) and imec in Belgium offers a postdoctoral position in NLP and machine learning.

Description of the project:
The successful candidate will work within the frame of a project, funded by the Brussels government, on NLP for healthcare. The project will acquire data from one of the largest hospitals in Brussels (UZ Brussels) and its aim is to perform automated clinical coding and nosocomial outbreak detection. To do so, two important aspects will be investigated: (i) multilingual NLP techniques and (ii) interpretation of NLP models to address tasks such as extreme classification and real-time prediction.

Responsibilities:
• Design and implement innovative algorithms within the aforementioned project,
• Publish the results at top-tier venues in NLP (e.g., ACL) and machine learning (e.g., ICLR), and
• Supervise junior researchers and support in teaching.

Profile and requirements:
• A PhD degree focusing on artificial intelligence, machine learning, and natural language processing or related;
• An excellent academic record with publications in top-tier scientific journals (e.g., TACL) and conference proceedings (e.g., ACL, EMNLP, AAAI);
• Proven programming experience (e.g., Python, C++);
• Fluency in state-of-the-art machine learning frameworks (e.g., Tensorflow, PyTorch);
• Fluency in English and excellent scientific writing and presentation skills;
• Ability and will to support teaching and to (co-)supervise bachelor, master and PhD students.

What we offer:
• A two-year position which upon positive evaluation can be further extended;
• A competitive salary (including holiday allowance) and benefits,
• An international scientific environment driven by excellence in fundamental research,
• Opportunities for travelling to conferences and research visits to international partner research groups (e.g., at Duke University, UCL)

How to apply:
Interested candidates should send: • a detailed curriculum vitae,
• a motivation letter related to the position’s profile,
• electronic copies of three key scientific publications, and
• the names of two potential referees

to the following contact person: Prof. Dr. Nikolaos Deligiannis via email at ndeligia@etrovub.be by March 29, 2020.

About the team:
The position is within Big Data team at the Department of Electronics and Informatics at Vrije Universiteit Brussel, Belgium. The team is also affiliated with imec, an international R&D and innovation hub in nanoelectronics and digital technologies.


Permanent research position in language technology at the Norwegian Computing Center, Oslo, Norway


We have a vacancy for a permanent research position in language technology at the Norwegian Computing Center (NR) in Oslo, Norway. We seek candidates with broad expertise in the field of NLP and the ability to work on different types of R&D projects. The position will be associated with the SAMBA research department, which currently has 45 researchers.

The researcher will be expected to participate in several research projects. In particular, we have recently initiated a large interdisciplinary research project on anonymization of textual data in collaboration with legal scholars, data security experts and researchers in health informatics. We also conduct research on spoken dialogue systems, human-robot interaction, multilingual language resources and information extraction on large amounts of texts. We also work closely with the University of Oslo, and many of our research projects are carried out in collaboration with various research groups in Norway and internationally.

You must be interested in applied research in language technology and machine learning. The applicant must hold a doctorate in language technology or computational linguistics, or a master degree combined several years of research experience. In addition, you must have good programming skills and the ability to work both independently and in teams.

Applicants must be fluent in English, both verbally and in writing. Knowledge of Norwegian or another Scandinavian language is an advantage, as several of our research projects focus on Norwegian text data. Experience in securing funding for R&D projects is also appreciated.

For more information, please visit the application website (in Norwegian).

We offer:
We offer a 100% permanent position, good salary conditions, pension and insurance schemes, flexible working hours, 5 weeks of holiday in addition to paid leave during Christmas and Easter, and our own staff canteen. Good training and development opportunities in an inspiring work environment together with colleagues in language technology, machine learning, statistical modelling and image analysis.

The Norwegian Computing Center is located in Kristen Nygaard's house at the Research Park at Blindern in Oslo. Negotiable starting date. We look forward to hearing from you.

About us:
Norsk Regnesentral (NR) is an independent, non-profit and non-profit private foundation that conducts contract research for business and public enterprises both in Norway and internationally. Our core research areas are statistical modelling, machine learning, artificial intelligence and ICT. Our clients are business and public administration, the EU and the Research Council of Norway.

The institute has 85 employees and is one of Europe's largest research institute within applied statistics. Major applications are petroleum, finance and insurance, earth observation, climate and environment, fisheries and aquaculture, health, image analysis and artificial intelligence. Research in ICT include cybersecurity, smart sensors, e-inclusion and universal design.


PostDoc or PhD in Secure and Robust Natural Language Processing, UKP Lab, Computer Science Department, TU Darmstadt

UKP Lab of the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

Associate Research Scientist "Secure and Robust NLP" (PostDoc- or PhD-level; for an initial term until the end of 2021)

as part of the National Research Center for Applied Cybersecurity ATHENE [1]. We are part of the research mission "SenPAI-Security and Privacy in AI". While AI becomes more common as a tool for various security applications where data must be analysed, clustered or attributed, the security of the applied AI algorithms is often limited. Various research results in the past years show shortcomings of trained neural nets (NN) like the lack of robustness against targeted attacks. The focus of our contribution to SenPAI is in (i) An automatic penetration testing system for NLP: A modular toolkit with common strategies to attack NLP models. This toolkit allows the wide-spread evaluation of state-of-the-art and in-production NLP systems; and (ii) Robust training objectives for NLP systems: State-of-the-art learning systems are equipped with the automatic attack toolkit in order to generate more robust NLP models. The goal is to have NLP models which are robust against new, unseen attacks and which require a higher effort to bypass them.

For this project, we are looking to hire a PostDoc or a PhD student with both a strong background in Natural Language Processing and a strong interest to contribute to applied security. We plan to cooperate with Fraunhofer SIT in Darmstadt and several other machine learning labs involved in SenPAI. The UKP Lab is a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, security and AI for Social Good in general.

We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining and strong interest in secure and robust NLP. Prior experience with neural network architectures, security-related applications and other relevant areas of NLP and Machine Learning is a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.

UKP Lab (cf. https://www.informatik.tu-darmstadt.de) provides a highly agile, diverse and supportive research environment. The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. Its unique profile around AI (cf. https://www.ai-da.tu-darmstadt.de) and information processing (cf. https://www.informatik.tu-darmstadt.de/aiphes) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.

To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by February 10th, 2020: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. Applications arriving after the deadline will still be considered until the position is filled.

[1] https://www.athene-center.de/en/


PhD or PostDoc in Natural Language Processing for the Social Good, Computer Science Department, TU Darmstadt

The Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

Associate Research Scientist "NLP for the Social Good" (PhD- or PostDoc-level; for an initial term until the end of 2022)

We are building a research profile in "Content Analytics for the Social Good" in close collaboration with multiple Machine Learning and Data Science labs as well as Social Science labs at the universities of Frankfurt and Mainz. To stregthen this profile, we are looking to hire a PhD student or a PostDoc with both a strong background in Natural Language Processing and a genuine interest to contribute to the Social Good, i.e. conduct research with decidedly positive impact on our society. Examples include privacy-aware NLP and large-scale text analysis to promote and enhance corporate social responsibility, public-policy making, or user empowerment under uncertainty. We specifically envisage cooperations with law and economics researchers and cutting-edge NLP research in low-resource scenarios.

The position is situated in a larger research environment of the UKP Lab as a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, and AI for Social Good in general. We have recently hired several postdocs to build a focus on NLP for the Social Good. The immediate supervision for the advertised position will be provided by Dr. Ivan Habernal. The strategic long-term advice will be given by Prof. Iryna Gurevych.

We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining and strong interdisciplinary interest in Computational Social Science. Prior experience with neural network architectures, corpus development and other relevant areas of NLP and Machine Learning is a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.

UKP Lab (cf. https://www.informatik.tu-darmstadt.de) provides a highly agile, diverse and supportive research environment. The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. Its unique profile around AI (cf. https://www.ai-da.tu-darmstadt.de) and information processing (cf. https://www.informatik.tu-darmstadt.de/aiphes) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.

To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by February 10th, 2020: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. Applications arriving after the deadline will still be considered until the position is filled.

NLP Research Internship at Adobe Research, San Jose, California

  • Employer: Adobe Research
  • Title: Research Scientist Intern
  • Speciality: NLP, search, dialog, joint NLP+computer vision
  • Location: San Jose, CA, USA
  • Deadline: Applications will be accepted until the position is filled.
  • Date posted: January 7, 2020
  • Contact: Franck Dernoncourt <franck.dernoncourt@adobe.com>

We are looking for PhD students with background in NLP, search, dialog, or joint NLP+computer vision for a spring/summer/autumn, ~13-week research internship (starting date and length are flexible). We strongly encourage our interns to publish their work to NLP/ML conferences/journals, and as a result we prefer candidates with a strong publication record. International PhD students are welcome to apply. Highly competitive salary. To apply, please send me an email with your CV (e.g., PDF or LinkedIn) as well as the list of your publications (e.g., PDF or link to your Google Scholar profile). You can view our NLP publications on https://research.adobe.com/publications/?a=natural-language-processing&y

Postdoctoral Researcher in NLP, School of Informatics, University of Edinburgh

  • Employer: University of Edinburgh
  • Title: Form-Independent Semantics for Natural Language Understanding
  • Specialty: NLP
  • Location: Edinburgh, United Kingdom
  • Deadline: 14th January 2020 at 5pm GMT
  • Date posted: 21st December 2019
  • Contact: Prof. Mark Steedman steedman@inf.ed.ac.uk

The position is to collaborate on research in question-answering using entailment graphs built by machine-reading and deep learning in Mark Steedman's lab in the Institute for Language, Cognition, and Computation (ILCC) at Edinburgh.

Details and application forms at: https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=050766


PhD Position in Neural NLG, Nancy, France as part of the EU Funded NL4XAI Innovative Training Network

  • Employer: CNRS
  • Title: Explainable Models for Natural Language Generation
  • Specialty: NLP, AI, Deep Learning
  • Location: Nancy, France
  • Deadline: February 14, 2020, at 23h59 CET (UCT + 01:00)
  • Date posted: December 17, 2019
  • Contact: claire.gardent@loria.fr

Estimated Starting Date: April 1, 2020

For more information, see https://members.loria.fr/CGardent/explainable-nlg.pdf

The EU funded NL4XAI Innovative Training Network is looking to employ a

Research Associate / PhD Candidate in Deep Learning and Natural Language Generation

The researcher will work under the supervision of Claire Gardent (https://members.loria.fr/CGardent/) at CNRS/LORIA/Lorraine University, Nancy (France) and be co-supervised by Albert Gatt (University of Malta); he or she will be expected to enrol for a PhD at Lorraine University (Nancy, France). Both Claire Gardent and Albert Gatt are leading experts on NLG. The researcher will be part of the Lorraine computer science research unit (LORIA) at Nancy, and work alongside other students and researchers who work on models for NLG. S/he will also benefit from the wider training and research network provided by the European NL4XAI Innovative Training Network (https://nl4xai.eu/).

During the course of the project, the researcher will carry out two 3 months-secondments to the University of Malta (with Albert Gatt) and one 3-months secondment to Orange in Lanion, France (with Lina Rohas-Barahona).

Claire Gardent has just been awarded an AI chair which focuses on multilingual and multisource NLG and will fund an additional 3 PhD students and an engineer over a period of 4 years (2020-2024). She also participates in the ANR Quantum Project on Question Generation (2019 – 2023) and heads the CNRS Research Network on Computational, Formal and Field Linguistics (2019 - 2023).

This is a great opportunity to join a leading NLG research group and work with top researchers to develop innovative techniques for NLG and explainable AI!

The NL4XAI project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860621.


11 Early Stage Artificial Intelligence Research Positions available in NL4XAI project (H2020-MSCA-ITN)

  • Employer: EU Funded NL4XAI Innovative Training Network
  • Title: 11 Early Stage Artificial Intelligence Research Positions available in NL4XAI project (H2020-MSCA-ITN)
  • Specialty: NLP, AI
  • Location: Europe
  • Deadline: February 14, 2020, at 23h59 CET (UCT + 01:00)
  • Date posted: December 17, 2019
  • Contact: josemaria.alonso.moral@USC.ES

Estimated Starting Date: April 1, 2020

Eleven PhD positions are offered within the framework of NL4XAI: Interactive Natural Language Technology for Explainable Artificial Intelligence, a project funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 860621.

NL4XAI is a European Training Network (ETN) project, which will train 11 creative, entrepreneurial and innovative early-stage researchers (ESRs), who will face the challenge of making Artificial Intelligence (AI) self-explanatory and thus contribute to translating knowledge into products and services for economic and social benefit, with the support of Explainable AI (XAI) systems.

The focus of NL4XAI is in the automatic generation of interactive explanations in natural language, just as humans naturally do, and as a complement to visualization tools. As a result, ESRs are expected to leverage the usage of AI models and techniques even by non-expert users.

The NL4XAI consortium is made up of 18 partners and beneficiaries from 6 different European countries (France, Malta, Poland, Spain, The Netherlands and the United Kingdom). The consortium is coordinated by the Research Centre in Intelligent Technologies of the Univ. of Santiago de Compostela (CiTIUS-USC) and the partners correspond to 2 national R&D centres (IIIA-CSIC and CNRS-LORIA), 10 universities (Univ. Aberdeen, TU Delft, Univ. Malta, Utrecht Univ., Univ. Twente, Univ. Lorraine, Univ. Dundee, Univ. Autònoma de Barcelona, Univ. Santiago de Compostela and Warsaw Univ. of Technology) and 6 private companies (Indra, Accenture, Orange, Wizenoze, Arria and Info Support).

Each ESR will work in an individual research project in a different host institution and will participate in academic and inter-sectoral secondments at the premises of other NL4XAI’s members.

We look for outstanding, motivated and team-spirited candidates to carry out a PhD within the NL4XAI ETN and who will get unique international and inter-sectoral training from prominent European researchers (from both academy and industry).

All details are available at: https://nl4xai.eu/


The NL4XAI project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860621.


Natural Language Processing and Machine Learning Scientist (KTP Fellow) in Manchester, UK

  • Employer: VoiceIQ and The University of Manchester, UK
  • Title: Natural Language Processing and Machine Learning Scientist (KTP Fellow)
  • Specialty: NLP, Machine Learning
  • Location: Manchester, UK
  • Deadline: January 13, 2020
  • Date posted: December 11, 2019
  • Contact: Sophia.Ananiadou@manchester.ac.uk

This is an exciting opportunity for an ambitious research scientist with expertise in Natural Language Processing and Machine Learning with the ability and confidence to work on a 30-month Knowledge Transfer Partnership (KTP) project with VoiceIQ Limited.

The project aims at developing innovative AI solutions to an exciting, high-impact and challenging problem of automatically detecting consumer vulnerability from communication channels by embedding state-of-the-art natural language processing and machine learning techniques.

VoiceIQ is an AI-powered, communications system, transforming enterprise telephony by leveraging the power of machine learning and natural language processing. The University of Manchester is among the world’s best universities (World 33 by Academic Ranking of World Universities 2019, World 27 by QS 2020).

The position will provide you with a unique opportunity to work in a rapidly growing UK based, AI software company and play a key role in the product development and commercial success of the company. You:

- Will apply and improve state-of-the-art machine learning and natural language processing techniques to address a cutting edge business problem which has a high level of commercial applicability;

- Will play a vital role in innovating, experimenting, developing and transferring such new techniques to VoiceIQ, publishing academic research discoveries in high impact fora in the field, and supporting strategically important future business development;

- Ultimately, will be responsible for creating a product that is new, first to the market and that will help protect vulnerable members of society from falling prey to mis-selling.

The position is particularly suitable for applicants who want to bridge academic and industrial research excellence.

You will require a PhD degree with an emphasis on machine learning applied to natural language processing or relevant subjects, and a few years of post-doc (or equivalent) experience. Experience relevant to deep learning and neural network-based learning models, to either text or speech analytics is essential.

This post is funded through a Knowledge Transfer Partnership (KTP) award, a UK Government scheme intended to promote sustained and mutually beneficial relationships between universities and Industry.

Based at VoiceIQ at Universal Square Business Centre in Manchester, the successful candidate will work directly with supervisors from both the University of Manchester and VoiceIQ and will use the facilities and resources of both organisations.

As an equal opportunities employer we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

FURTHER DETAILS AND APPLICATION FORM - https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=18367

Associate Research Scientist, UKP Lab, TU Darmstadt

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

Associate Research Scientist (PostDoc- or PhD-level; for an initial term of two years)

We are looking to strengthen our group’s profile in a set of emerging areas of Machine Learning and Natural Language Processing (NLP). Examples include human-in-the-loop machine learning, argument mining and claim validaton, conversational AI, or multimodal commonsense reasoning. UKP Lab is a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, and AI for Social Good in general.

We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining. Prior experience with neural network architectures, reinforcement learning and other relevant areas of NLP and Machine Learning are a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.

UKP Lab (cf. https://www.informatik.tu-darmstadt.de) provides a highly agile, diverse and supportive research environment. The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. Its unique profile around AI (cf. https://www.ai-da.tu-darmstadt.de) and information processing (cf. https://www.informatik.tu-darmstadt.de/aiphes) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.

To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by December 11th, 2019: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. Applications arriving after the deadline will still be considered until the position is filled.


Tenure-Track/Tenured Faculty Positions: The University of Texas at Arlington

  • Employer: Department of Computer Science and Engineering, The University of Texas at Arlington
  • Title: Assistant/Associate Professor
  • Speciality: AI / Machine Learning / Robotics, Cyber Physical Systems
  • Location: Arlington, TX, USA
  • Deadline: Review of applications will start November 15, 2019 and will continue until the positions are filled.
  • Contact: Christoph Csallner (csallner@uta.edu), Chengkai Li (cli@uta.edu)
  • Date posted: November 9, 2019
  • Website: https://cse.uta.edu/faculty-positions/tenure-track.php

The Computer Science and Engineering Department at The University of Texas at Arlington invites applications for 3 tenure-track/tenured assistant/associate professor positions with a tentative start date in Fall 2020. The areas of the following position titles are intended to be interpreted broadly (e.g., "Cyber Physical Systems" may include embedded systems, hybrid systems, sensors, vision, IoT, cybersecurity, feedback systems, actuation, digital fabrication, and related areas):

  • Assistant/Associate Professor - AI / Machine Learning / Robotics
  • Assistant Professor - Cyber Physical Systems
  • Assistant/Associate Professor - Cyber Physical Systems

Our key objective is to hire faculty members with outstanding qualifications, who share the university's core values of high standards of excellence in teaching, innovative research, and service, combined with fostering an open and inclusive environment and promoting diversity and participation of groups that are currently underrepresented in engineering fields. A major emphasis will be potential research collaboration within and outside the department.

Application Instructions

To apply, please go to https://uta.peopleadmin.com/postings/10800 and submit the following materials: cover letter, curriculum vitae, research plans, teaching philosophy, and contact information of at least three references (at least five references for Associate Professor candidates). Senior candidates should also include unofficial course evaluations. All candidates should also include a statement of contribution to diversity, equity, and inclusion.

Review of applications will start November 15, 2019 and will continue until the positions are filled.

Questions about the openings should be addressed to cli@uta.edu or csallner@uta.edu.

EEO/AA Policy

UTA is an Equal Opportunity/Affirmative Action institution. Minorities, women, veterans and persons with disabilities are encouraged to apply. Additionally, the University prohibits discrimination in employment on the basis of sexual orientation. A criminal background check will be conducted on finalists. UTA is a tobacco free campus.


Tenure Track Faculty Positions: Johns Hopkins University

  • Employer: Department of Computer Science, Johns Hopkins University
  • Title: Assistant/Associate/Full Professor
  • Speciality: All areas of Computer Science
  • Location: Baltimore, Maryland, USA
  • Deadline: December 15, 2019
  • Contact: Mark Dredze (mdredze@cs.jhu.edu)
  • Date posted: October 31, 2019
  • Website: https://www.cs.jhu.edu/about/employment-opportunities/

http://apply.interfolio.com/69225

The Johns Hopkins University’s Department of Computer Science seeks applicants for tenure-track faculty positions at all levels and across all areas of computer science. The department will consider offers in two tracks: (1) an open track seeking excellent candidates across all areas of computer science; and (2) a track seeking candidates in the areas of human computer interaction (HCI), human AI interaction, computational health, artificial intelligence and machine learning. The search will focus on candidates at the junior level, but all qualified applicants will be considered.

Plans for faculty growth in the department are aligned with School and University initiatives in health and AI. Additionally, the faculty will continue to grow by adding excellent and diverse candidates across all areas of computer science. The HCI search is part of a newly-launched initiative (http://hci.jhu.edu) that seeks to transform existing HCI research activities across the university by making several faculty hires within Computer Science.

The Department of Computer Science has 31 full-time tenured and tenure-track faculty members, 8 research and 5 teaching faculty members, 200 PhD students, 200 MSE/MSSI students, and over 500 undergraduate students. There are several affiliated research centers and institutes including the Laboratory for Computational Sensing and Robotics (LCSR), the Center for Language and Speech Processing (CLSP), the JHU Information Security Institute (JHUISI), the Institute for Data Intensive Engineering and Science (IDIES), the Malone Center for Engineering in Healthcare (MCEH), the Institute for Assured Autonomy (IAA), and other labs and research groups. More information about the Department of Computer Science can be found at www.cs.jhu.edu and about the Whiting School of Engineering at https://engineering.jhu.edu.

Applicants should submit a curriculum vitae, a research statement, a teaching statement, three recent publications, and complete contact information for at least three references.

Applications must be made on-line at http://apply.interfolio.com/69225. While candidates who complete their applications by December 15, 2019 will receive full consideration, the department will consider applications submitted after that date.

The Whiting School of Engineering and the Department of Computer Science are committed to building a diverse educational environment: https://www.cs.jhu.edu/diversity/.

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the University does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The University is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved.


Assistant Professor with emphasis on Natural Language Processing, University of Georgia

  • Employer: Department of Computer Science, University of Georgia
  • Title: Assistant Professor
  • Speciality: NLP unspecified
  • Location: Athens, Georgia, USA
  • Deadline: November 13 2019
  • Contact: Krzysztof J. Kochut (kkochut@uga.edu)
  • Date posted: October 24th 2019

Assistant Professor with emphasis on Natural Language Processing

The Department of Computer Science at the University of Georgia invites applications for a tenure-track assistant professor position, starting August 2020. This position will complement and further strengthen our department’s research and education efforts in Natural Language Processing and offers a competitive salary and generous startup package. Applicants should hold a Ph.D. in Computer Science or related field.

The ideal candidate for this position will have a strong research background in Natural Language Processing, and be committed to excellence in both research and teaching.

Computer Science is a growing and congenial department of 35 faculty within the Franklin College of Arts and Sciences. The department has more than 1,150 undergraduate and more than 200 graduate students and offers the B.S., M.S., and Ph.D. degrees in CS. The teaching load allows for substantial concentration on research. In addition to the areas in which we are recruiting, our faculty cover a broad range of research interests, including algorithms, artificial intelligence, bioinformatics, brain imaging and mapping, computer security, computational science and high-performance computing, computer vision, data privacy, data science, distributed and real-time systems, machine learning, parallel and distributed computing, robotics, simulation, and semantic web. Please see http://www.cs.uga.edu for more information about the department and the university.

The Franklin College of Arts and Sciences, its many units, and the University of Georgia are committed to increasing the diversity of its faculty and students, and sustaining a work and learning environment that is inclusive. Women, minorities, protected veterans and individuals with disability are encouraged to apply. The University of Georgia is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, ethnicity, age, genetic information, disability, gender identity, sexual orientation, or protected veteran status. Persons needing accommodations or assistance with the accessibility of materials related to this search are encouraged to contact Central HR (hrweb@uga.edu). Please do not contact the department or search committee with such requests. The University of Georgia (UGA), a land-grant and sea-grant university with statewide commitments and responsibilities is the state's oldest, most comprehensive and most diversified institution of higher education (http://www.uga.edu). UGA is currently ranked among the top 20 public universities in U.S. News & World Report. The University's main campus is located in Athens, approximately 65 miles northeast of Atlanta, with extended campuses in Atlanta, Griffin, Gwinnett, and Tifton. UGA was founded in 1785 by the Georgia General Assembly as the first state-chartered University in the country. UGA employs approximately 2,348 full-time faculty and more than 8,980 full-time staff. The University's enrollment exceeds 37,500 students including over 28,800 undergraduates and over 8,700 graduate and professional students. Academic programs reside in 17 schools and colleges, as well as a medical partnership with Augusta University housed on the UGA Health Sciences Campus in Athens.

To apply, please go to http://www.ugajobsearch.com/postings/121338. Please upload a cover letter, curriculum vitae, and short statements of research interests and teaching philosophy. Please provide contact information (email and telephone number) for three references. Review of applications will begin on November 13, 2019 and will continue until the position is filled.

Assistant or Associate Professor, Dept. Information Systems and Cyber Security, University of Texas at San Antonio

  • Employer: The University of Texas at San Antonio
  • Title: Assistant or Associate Professor of Information Systems and Cyber Security
  • Specialty: NLP, text mining, machine learning, data science, or cyber security
  • Location: San Antonio, Texas, USA
  • Deadline: Open until filled
  • Date posted: 21 October 2019
  • Contacts: Anthony Rios, (anthony.rios@utsa.edu)

The University of Texas at San Antonio Department of Information Systems and Cyber Security

The University of Texas at San Antonio Department of Information Systems and Cyber Security invites applicants for a tenure-track position (rank: Assistant or Associate) beginning Fall 2020.

The position requires a Ph.D. degree in Information Systems, Cyber Security or related areas (e.g., Information Science, Computer Engineering, Computer Science, etc.) with a strong preference for a specialization in Data Analytics (e.g., machine learning, information retrieval, natural language processing, computational social science, etc.) or a specialization in Cyber Security. Candidates whose work lies at the intersection of Data Analytics and Cyber Security (e.g., anomaly detection in computing system data, artificial intelligence informed cyber situational awareness, etc.) are particularly encouraged to apply. Candidates must demonstrate strong potential for publishing in top-tier Information Systems, Data Analytics or Cyber Security publication venues. The successful candidate must demonstrate their ability to work with and be sensitive to the educational needs of diverse urban populations and support the university’s commitment to thrive as a Hispanic Serving Institution and a model for student success. Candidates will be expected to participate in departmental service activities. Candidates are also expected to participate in pursuing cross-disciplinary research grants. The ability to obtain and conduct federally-funded research that requires a top-secret security clearance is preferred. Responsibilities include research, teaching at the graduate and undergraduate levels and program development. The Department of Information Systems and Cyber Security consists of 14 tenured and tenure-track faculty members. Salary and benefits are competitive and commensurate with qualifications and experience. For additional information about the position, visit https://business.utsa.edu/faculty-and-research/faculty-openings/.

Applicants must submit their full application package via the STARS program which is located at https://jobs.utsa.edu/.

Applications will be accepted until the position is filled. Questions may be directed to Dr. Anthony Rios, chair of the search committee, at Anthony.Rios@utsa.edu. Tenured appointments are contingent upon Board of Regents approval. Applicants who are selected for interviews must be able to show proof that they will be eligible and qualified to work in the United States by time of hire. UTSA is an Affirmative Action/Equal Opportunity Employer. Women, minorities, veterans and individuals with disabilities are encouraged to apply.


Assistant Professor in Computational Linguistics, Dept. of Linguistics, University of Colorado at Boulder

  • Employer: University of Colorado
  • Title: Assistant Professor of Linguistics
  • Specialty: Computational Linguistics
  • Location: Boulder, Colorado, USA
  • Deadline: 1 November 2019
  • Date posted: 07 October 2019
  • Contacts: Martha Palmer or Mans Hulden, (martha.palmer@colorado.edu)

The Department of Linguistics at the University of Colorado Boulder seeks applications for an Assistant Professor tenure-track faculty position in Computational Linguistics beginning Fall 2020. Within Computational Linguistics we are particularly interested in candidates who use computational methods to address enduring questions in syntax, semantics and/or pragmatics, and other core areas of linguistics. We envision potential applications to Natural Language Processing and/or to discourse and dialogue advances that could be relevant to Human-Computer Interaction. Our primary consideration is the originality, intellectual breadth, and promise of the candidate’s work. This position will complement the strong, interdisciplinary cohort of Computational Linguistics faculty at CU and be affiliated with both our Center for Computational Language and EducAtion Research (CLEAR), and our cross-college Professional MS in Computational Linguistics, Analytics, Search and Informatics (CLASIC). The successful candidate will also benefit from our interdisciplinary partnerships with the Institute of Cognitive Science. We are especially interested in qualified candidates who can contribute, through their research, teaching, and service, to the diversity and excellence of our academic community.

Full consideration will be given to applications that are completed by November 1, 2019. Applications will be accepted until February 15, 2020.

For more details see:

https://jobs.colorado.edu/jobs/JobDetail/?jobId=20950


Assistant Professor of Linguistics, Dept. of Linguistics, University of Kentucky

  • Employer: University of Kentucky
  • Title: Assistant Professor of Linguistics
  • Specialty: Computational Linguistics
  • Location: Lexington, Kentucky, USA
  • Deadline: 18 November 2019
  • Date posted: 07 October 2019
  • Contacts: Mark Richard Lauersdorf (lauersdorf@uky.edu)

The Department of Linguistics at the University of Kentucky in Lexington, Kentucky invites applications for a tenure track position at the rank of Assistant Professor of Linguistics to begin August 2020. The ideal candidate will have demonstrated research expertise using the tools and methodologies of computational linguistics in pursuit of theoretical linguistic questions, and an ability to teach courses in a range of computational and theoretical areas. We encourage candidates who apply computational methods in one or more of the following areas: syntax, semantics, phonology, phonetics, sociolinguistics, or historical linguistics. As a department and university, we are strongly committed to creating an inclusive and effective teaching, learning, research, and working environment for all.

Responsibilities of the position include pursuing an active research program and teaching a total of four courses per year at the introductory, advanced undergraduate, and graduate levels. Responsibilities also include active participation in the academic life of the department, collaboration with units across campus (e.g., Computer Science, Modern and Classical Languages, Hispanic Studies), pursuing external funding, and providing service to the university and the discipline. Applicants are expected to have completed their PhD by August 2020.

Interested applicants should apply online at: http://ukjobs.uky.edu/postings/251804. Applicants should submit the following: (1) letter of application, (2) current CV, (3) research statement (1-2 pages in which applicant describes current and future research agenda; upload as Specific Request 1), (4) a recent writing sample, (5) teaching statement (1-2 pages in which applicant discusses teaching philosophy and experiences; upload as Specific Request 2), and (6) a diversity statement (1-2 pages in which applicant reflects on commitments, approaches, and insights related to inclusion, diversity, and equity; upload as Specific Request 3). In addition, please provide the names and contact information for three references when prompted in the academic profile. This information may be utilized to solicit recommendation letters from your references within the employment system at a more advanced stage of the application process.

All applications will be acknowledged. Deadline for the receipt of applications is November 18, 2019.

For any questions relating to this position, please contact the chair of the search committee, Mark Richard Lauersdorf, at lauersdorf@uky.edu.

The University of Kentucky is an Equal Opportunity Employer and encourages applications from veterans, individuals with disabilities, women, African Americans, and all minorities.


Postdoctoral Research Fellow on Sloan-sponsored NLP project, University of California, Berkeley

  • Employer: UC Berkeley
  • Title: Postdoctoral Fellow
  • Specialty: NLP, definition recognition, text equation analysis, information retrieval
  • Location: Berkeley, CA, USA
  • Deadline: Open until filled
  • Date posted: September 17, 2019
  • Contacts: Marti Hearst (hearst@berkeley.edu)

UC Berkeley’s School of Information and CS Division seeks a Postdoctoral Fellow to conduct research and algorithm development in Natural Language Processing, with a sub-interest in Information Retrieval or Citation Analysis. This position funds a researcher to work alongside Prof. Marti Hearst on a Sloan-funded project whose goal is to develop intelligent interfaces to the AI scientific literature, in collaboration with researchers and developers at AI2’s Semantic Scholar project. The Postdoctoral Fellow will develop novel algorithms and software to identify definitions within and between scientific papers in the co-citation network, analyze textual descriptions of mathematical notation, and other relevant NLP and IR research problems. This ambitious project provides an opportunity to test research results with tens of thousands of users in an open source environment.

The Postdoctoral Fellow position requires a terminal degree appropriate to your discipline. The pos­ition does not have a teaching requirement, but if desired, the Fellow will have opportunities to teach and mentor both undergraduate and graduate students. The Fellow will be viewed as a colleague, and with mentorship, will be launched to the next career stage.

Applicants should have experience conducting independent research, demonstrate a record of developing algorithms and supporting software, communicating research via publications and presentations, be excited about the goals of the project and about participating in collaborative, interdisciplinary research. Applicants must have defended their PhD in Computer Science, Information Science, or a related field by the time of employment.

Applicants should have interests in one or more of the following areas: natural language processing, co-citation analysis, information retrieval. The ideal candidate is deeply interested in analyzing the text of documents via detecting and/or generating explanations and definitions within and between documents in a co-citation network. A background or interest in human computer interaction is a strong additional qualification.

How do I apply? Interested candidates should prepare a single pdf file containing: (1) a cover letter stating background, experience, interest in the position, and career objectives, (2) a curriculum vitae or résumé, including a link to a web page with publications and other relevant information (3) the names and contact information for three references who can write a letter on your behalf, and (4) a relevant sample of published work. Send application materials to Prof. Marti Hearst (hearst@berkeley.edu) with the subject line: NLP postdoc application.

How much does the position pay? The University classifies this as a Postdoctoral position. All recipients receive a salary of US $60,000/year for full-time employment as well as full benefits (https://vspa.berkeley.edu/postdoc-health-insurance-and-benefits). Additional funds are available for equipment and professional travel.

When can I apply? Review of applications will begin on October 15, 2019 and will continue until the position is filled.

When does the position start? January 2, 2020 is the preferred start date, although it can start earlier, but we can be flexible depending on other factors. The position will be for one year with possible extension for an additional half year.

Will foreign applicants be considered? Yes. We highly encourage students from underrepresented groups to apply. UC Berkeley is an Equal Employment Opportunity (EEO) employer and welcomes all qualified applicants. Applicants will receive fair and impartial consideration without regard to race, sex, color, religion, national origin, age, disability, veteran status, genetic data, or other legally protected status.



Research professor, Department of Computer Science, KU Leuven, Belgium

  • Employer: KU Leuven
  • Title: Research professor
  • Specialty: Representation learning for natural language and multimedia processing
  • Location: Leuven, Belgium
  • Deadline: September 20, 2019
  • Date posted: September 4, 2019
  • Contact: Sien Moens (Sien.Moens@cs.kuleuven.be)

The Department of Computer Science at KU Leuven has a full-time academic vacancy in the area in natural language and multimedia processing. The position is a research professorship with strongly reduced teaching responsibilities for the first 10 years. We seek applications from internationally oriented candidates with an outstanding research track record and excellent didactic skills. The successful candidate will perform research in the Human-Computer Interaction research group. The appointment is expected to start on October 1, 2020.

More information is available at https://www.kuleuven.be/personeel/jobsite/jobs/55192105?hl=en&lang=en .

Postdoctoral researcher, KU Leuven, Belgium

  • Employer: Department of Computer Science, KU Leuven
  • Title: Postdoctoral researcher
  • Speciality: Representation learning in the context of natural language understanding
  • Location: Leuven, Belgium
  • Deadline: October 15, 2019
  • Date posted: September 4, 2019
  • Contact: sien.moens@cs.kuleuven.be


We offer a two-year postdoctoral position (extendable to four years) funded by the ERC (European Research Council) Advanced Grant CALCULUS “Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding” (http://calculus-project.eu). The position focuses on natural language understanding but gives possibilities to research topics in one or more of the following fields: machine learning (especially semi-supervised learning, transfer learning, continual learning, deep learning and latent variable models), multimodal processing of language and visual data, learning the grounded meaning of language from various contexts in which language is used (e.g., physical, language and social), representation learning at the word, phrase, sentence or discourse level considering various contexts, learning commonsense knowledge about the world from multimodal data, multimodal grammar induction, and inference models for language understanding. The successful candidate will work on innovative natural language understanding research. He or she will be given the opportunity for personal development beyond research, for example by contributing to teaching (e.g., at the undergraduate and graduate levels).


Postdoctoral fellow on IBM-sponsored NLP for human microbiome project, UC San Diego

  • Employer: UC San Diego
  • Title: Postdoctoral Fellow
  • Specialty: NLP, text mining, knowledge base construction
  • Location: La Jolla, CA, USA
  • Deadline: Open until filled
  • Date posted: August 22, 2019
  • Contacts: Daniel Freed (CMIinfo@ucsd.edu)

The automatic knowledge base construction group in the UC San Diego-IBM Artificial Intelligence for Healthy Living (AIHL) program, led by Dr. Chun-Nan Hsu and Dr. Rob Knight, is seeking applications of a Postdoctoral Fellow in deep learning for natural language processing to extract microbiome knowledge from the scientific literature. The positions are available immediately. The project will be funded on a contract for three years. The research group is part of the Center for Microbiome Innovation (CMI), one of the top research centers in the world in human microbiome research, developing AI, deep learning, and cutting edge data sciences to advance the understanding of the impact of microbiome to health. The knowledge base group has developed one of the most efficient and accurate algorithms in automated understanding of disease mentions in the scientific literature, winning the Best Application Award in the 2019 conference of Automated Knowledge Base Construction (AKBC). Our former master student was admitted to prestigious PhD programs with fellowships. The group resides in the Qualcomm Institute (UC San Diego division of the California Institute for Telecommunications and Information Technology (Calit2)), the home of multidisciplinary research programs and startups at UCSD. The group has access to powerful GPU computer clouds at CMI and IBM. The group strives to deliver useful knowledge base systems and develop original, innovative, top-tier conference acceptable algorithms simultaneously. Group members work closely with CMI faculties and students and top-notch researchers from IBM in the Bay Area and around the world through frequent virtual and face-to-face meetings. The postdoctoral fellow will be encouraged to take initiation to explore new ideas to accomplish fully automatic knowledge base construction for human microbiome and work on grant proposals to develop into an independent leader of scientific research.

Scope of research:

  • Learning from structured ontologies
  • Unsupervised, weakly supervised machine learning and active learning for NLP
  • Biomedical concept understanding
  • Event and relation extraction and inference

Qualifications:

  • Ph.D. in a relevant discipline, including in the areas of natural language processing, machine learning, or bioinformatics and systems biology
  • Strong record in publications in top-tier AI conferences and Bioinformatics journals
  • Undergraduate or graduate coursework or degree in Biology or a related field is a plus

How to Apply: Please email a completed application form (http://cmi.ucsd.edu/PostDocApplication) and support documents to CMIInfo@ucsd.edu to apply.

Note: If you have relatives employed at UC San Diego, you must include the name, relationship and department where employed in your resume or cover letter. This information is used only for the purpose of complying with the University’s nepotism policy.

Postdocs on Facebook-sponsored neural NLG project, Ohio State University

  • Employer: The Ohio State University
  • Title: Postdoctoral Scholar
  • Specialty: NLG, conversational systems, NLP
  • Location: Columbus, OH, USA
  • Deadline: August 18, 2019
  • Date posted: August 2, 2019
  • Contacts: Michael White (mwhite@ling.osu.edu)

Multiple postdoctoral scholar positions are open at Ohio State for a Facebook-sponsored project on natural language generation in conversational system with the theme of structure in neural NLG.

Full details are available on the application page: https://www.jobsatosu.com/postings/96937

Open Rank Professor, iSchool and Department of Criminology and Criminal Justice, University of Maryland

  • Employer: University of Maryland
  • Title: Open Rank Professor
  • Specialty: Data-driven analyses in crime, law and justice
  • Location: College Park, MD
  • Deadline: October 1, 2019 (deadline for full consideration, late applications may be accepted)
  • Date posted: July 26, 2019
  • Contacts: Katie Shilton (kshilton@umd.edu) and Laura Dugan (ldugan@umd.edu)

The College of Information Studies (Maryland’s iSchool) and the Department of Criminology and Criminal Justice at the University of Maryland, College Park invite applications for an open rank tenure-track or tenured faculty position with a focus on building systems for and conducting data-driven analyses in crime, law and justice. Examples of possible research approaches include: data mining; information visualization; automating or advancing data pre-processing; signal processing, computer vision, and natural language processing; applied machine learning; algorithmic transparency, debiasing algorithms and data, and algorithmic accountability; and computational social science.

We are interested in candidates who apply these topics in the context of criminology, justice, and criminal law (e.g., predictive policing, pretrial risk assessment, database building through open sources, linking criminal records, recidivism prediction, management of bodycam video, face recognition in surveillance images, management of DNA evidence). Candidates with data-driven approaches to related social science topics are encouraged to apply.

Applicants should apply electronically at https://ejobs.umd.edu/postings/71777.

Tenure-track Assistant Professor of Computational Linguistics, Boston University

  • Employer: Boston University
  • Title: Assistant Professor
  • Specialty: Computational Linguistics
  • Location: Boston, MA
  • Deadline: October 20, 2019 (deadline for full consideration, late applications may be accepted)
  • Date posted: July 24, 2019
  • Contact: Carol Neidle <carol@bu.edu>

The Boston University Linguistics Department seeks a tenure-track Assistant Professor of Computational Linguistics (for primary appointment in Linguistics, secondary appointment in or affiliation with Computer Science), beginning July 1, 2020, pending budgetary approval; to conduct research, teach courses in Computational Linguistics and related areas (Linguistics, Computer Science) at introductory and advanced levels, and advise graduate and undergraduate students. Should have excellent programming skills and experience in computational linguistic research. Experience in application of computational methods to field linguistics or analysis of understudied languages would be a plus. Requirements include PhD in Linguistics (preferred) or Computer Science in hand by start date, with strong background in both fields, and demonstrated excellence in teaching, advising, and research. For further information: http://ling.bu.edu/ and http://www.bu.edu/cs/ .

Applications should be uploaded through https://academicjobsonline.org/ajo/jobs/14064. Full details of application requirements, as well as a statement of the university’s commitment to diversity and inclusion, are available on that site.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. We are a VEVRAA Federal Contractor.


Full-Time Research Engineer, New York University

  • Employer: New York University
  • Title: Research Engineer
  • Specialty: Open-source software, pretraining and transfer learning
  • Location: New York, USA
  • Deadline: July 31, 2019 (deadline for full consideration, late applications may be accepted)
  • Date posted: July 17, 2019
  • Contact: Sam Bowman <bowman@nyu.edu>

'm hiring a full-time research engineer. If you're interested in transitioning from software engineering to NLP/ML research, and you'd be up for a stint in an academic lab, there's more information and an application from here: https://apply.interfolio.com/65666

PhD in Biomedical Information Extraction, The University of Manchester, UK

  • Employer: University of Manchester
  • Title: PhD in Biomedical Information Extraction
  • Specialty: Natural Language Processing, Text Mining, Machine Learning
  • Location: Manchester, UK
  • Deadline: May 26, 2019
  • Date posted: May 10, 2019
  • Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk>

The National Centre for Text Mining (http://www.nactem.ac.uk), School of Computer Science in collaboration with the Faculty of Biology, Medicine and Health, The University of Manchester, offer a PhD scholarship to advance research in neural information extraction applied to cancer mechanisms.

Candidates must have a minimum upper second class first degree in Computer Science and an MSc in Computer Science or a related discipline. Experience in machine learning and neural networks applied to NLP are highly desirable, as is the ability to work in an interdisciplinary setting.

Further information can be obtained here: http://nactem.ac.uk/newsitem.php?item=393

PhD in Biomedical Information Extraction, The University of Manchester, UK

  • Employer: University of Manchester
  • Title: PhD in Biomedical Information Extraction
  • Specialty: Natural Language Processing, Text Mining, Machine Learning
  • Location: Manchester, UK
  • Deadline: May 26, 2019
  • Date posted: May 10, 2019
  • Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk>

The National Centre for Text Mining (http://www.nactem.ac.uk), School of Computer Science in collaboration with the Faculty of Biology, Medicine and Health, The University of Manchester, offer a PhD scholarship to advance research in neural information extraction applied to cancer mechanisms.

Candidates must have a minimum upper second class first degree in Computer Science and an MSc in Computer Science or a related discipline. Experience in machine learning and neural networks applied to NLP are highly desirable, as is the ability to work in an interdisciplinary setting.

Further information can be obtained here: http://nactem.ac.uk/newsitem.php?item=393


24-month Postdoctoral Position, IRISA (France, Lannion), Paraphrase Generation / Natural Language Generation

  • Employer: University of Rennes 1
  • Title: Postdoctoral Researcher
  • Specialty: Natural language processing
  • Duration: 24 months
  • Location: Lannion, France
  • Deadline: until filled
  • Date posted: April 23, 2019
  • Contact: Gwénolé Lecorvé (gwenole.lecorve@irisa.fr), Jonathan Chevelu (jonathan.chevelu@irisa.fr)

Overview

IRISA [1] is the largest research laboratory dedicated to computer science in France, hosting more than 800 people and 40 research teams. Its activities spans all the fields of computer science. It is located in Rennes, Lannion, and Vannes.

The Expression team [2] works on natural language processing (NLP), be it through texts, speech or gestures. In particular, it focuses on the expressive components of the human languages.

The opened position is part of the ANR TREMoLo project [3] hosted by the team and aimed at transforming the language register of texts, for instance mapping a text from the formal register to the casual one. This involves work on linguistic characterization, pattern mining and paraphrase generation. The activities are conducted on the French language.

The recruited person will work on a paraphase generation and propose solution to integrate register-specific stylistic constraints. She/he is expected to investigate on the use of statistical and neural paraphrasing systems, that is:

  • Training of a baseline systems using either statistical or neural approaches.
  • Intregration of constraints formulated as sequential patterns.
  • Organization of evaluation campaigns.

Job requirements

  • PhD in natural language processing or machine learning
  • Top academic and publication records
  • Good communication skills
  • Team work experience
  • Knowledge in French is a plus but is not required.

Postdoctoral Position Available in Natural Language Processing and Human-Robot Interaction, Army Research Lab

  • Employer: US Army Research Laboratory
  • Title: Postdoctoral Researcher
  • Specialty: Natural language processing, human-robot interaction, dialogue systems
  • Location: Adelphi, Maryland, United States with ~8 weeks of travel per year to Boston
  • Deadline: April 30, 2019 (or until filled)
  • Date posted: April 15, 2019
  • Contact: Matthew Marge (matthew.r.marge.civ@mail.mil)

Overview

The US Army Research Laboratory (ARL) is welcoming applications for a one-year renewable (up to 3 years) postdoctoral position at the intersection of natural language processing (NLP) and human-robot interaction (HRI), focusing on dialogue with robots. The successful candidate will contribute to the research and development of the project, “Learning about the Physical World Autonomously through Information-Theoretic Dialogue”, funded by the Office of the Secretary of Defense's Laboratory University Collaboration Initiative (LUCI) Fellowship. The goal of the project is to investigate techniques for robots to learn, from natural language dialogue, about objects and actions in the physical world.

In support of this effort, ARL is looking for an individual with a PhD or equivalent experience, with interest and a background in human-robot interaction, natural language processing, symbol grounding, and/or dialogue systems. We plan to develop an approach to detecting uncertainty about objects and actions using multiple modalities (e.g., language and vision), so that robots can initiate natural language questions that humans can answer that maximize the agent's information gain in a situation.

The project is supervised by Dr. Matthew Marge (ARL), with co-PI Dr. Gordon Briggs (NRL), and faculty collaborator Prof. Matthias Scheutz (Tufts University). The successful candidate will collaborate with the PIs on designing human-robot interaction experiments and developing techniques to support human-robot dialogue systems.

The position is available immediately with a duty station at the Adelphi Laboratory Center (ALC), Adelphi, MD (Washington, D.C. metro area), with extended travel (~8 weeks per year) to Boston, MA to visit the Human-Robot Interaction Lab at Tufts University and periodic travel to the Laboratory for Autonomous Systems Research at the Naval Research Laboratory, Washington, D.C.

Job requirements:

  • Ph.D. or equivalent research experience in computer science, artificial intelligence, computational linguistics, human-robot interaction, computer engineering or related field.
  • U.S. citizenship is preferred.

To learn more about this position, or to apply, please send questions or a CV to Dr. Matthew Marge at matthew.r.marge.civ@mail.mil.

Associate Research Scientist in Natural Language Processing, UKP Lab, TU Darmstadt

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

Associate Research Scientist
(PhD-level; for an initial term of two years)

This position should further strengthen the group’s profile in one or more areas of Natural Language Processing (NLP), such as natural language generation, semantics and discourse processing, or multi-document information consolidation.

UKP Lab is a research group comprising over 30 team members who work on various aspects of data-driven NLP and machine learning with their novel applications in various domains, e.g. conversational IR systems, scientific literature analysis, or social media mining.

We ask for applications from candidates in Computer Science with a specialization in Natural Language Processing or Text Mining, preferably with prior expertise in the relevant areas of computer science and strong programming skills. Experience with neural network architectures and demonstrable engagement in open source projects are strong advantages. Strong communication skills in English are a must.

UKP’s provides an excellent cooperation network with both top academic and industrial partners in Artificial Intelligence (AI), and a supportive research environment within the lab. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique profile around AI and the DFG-funded Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) emphasize NLP, machine learning, and scalable infrastructures for the assessment and aggregation of information. UKP Lab is a high-profile research group committed to cutting-edge research, dynamic operations, cooperative work style and close interaction of team members. The selected candidates will have an opportunity for professional growth according to their seniority level.

Applications should include a detailed CV, a motivation letter and an outline of previous work or research experience (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference.

Please submit your application via the following form by April 30th, 2019: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.

Senior Research Scientist - Natural Language Processing at Bosch Research

  • Employer: Bosch Research
  • Title: Senior Research Scientist (Principal level position also available)
  • Specialties: Natural language processing, natural language understanding, information retrieval, question answering, information extraction.
  • Location: Sunnyvale, CA, USA
  • Deadline: N/A (The position is open until filled)
  • Date Posted: March 7, 2019
  • Website: http://smrtr.io/_cXw

Company Description

The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania and Cambridge, Massachusetts is part of the global Bosch Group (www.bosch.com), a company with over 70 billion euro revenue, 400,000 people worldwide, a very diverse product portfolio, and a history of over 125 years. The Research and Technology Center North America (RTC-NA) is committed to providing technologies and system solutions for various Bosch business fields primarily in the areas of Human Machine Interaction (HMI), Robotics, Energy Technologies, Internet Technologies, Circuit Design, Semiconductors and Wireless, and MEMS Advanced Design. In all areas we work in close collaboration with our partners at leading US universities, leading-edge industry partners, and other worldwide Bosch research, development, and marketing units.

The focus of our global HMI research includes Visual Computing, Audio and Language Computing, Conversational AI, Smart Wearables and Haptics, User Experience (UX) and Human Factors, etc. We develop intuitive, interactive and intelligent solutions to enable an inspiring UX for Bosch products and services in application areas such as autonomous driving, car infotainment and driver assistance systems (ADAS), Industry 4.0 and Internet of Things (IoT), security systems, smart home and building solutions, health care, and robotics.

As a part of the global Human Machine Interaction research unit, our Language and Audio Computing group is responsible for shaping the future user experience of Bosch products by developing cutting-edge technologies and prototype systems in the fields of text and audio processing, including natural language processing, natural language understanding, question answering, information retrieval, and audio signal processing. We work on solutions to hard challenges of truly understanding the human language and audio signals, extracting the semantics from text and audio, and enabling natural, intuitive and intelligent HMI and personal assistance. We work with internal partners at various Bosch business units to transfer our ideas and solutions into future products. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals, e.g., ACL, EMNLP, NAACL, COLING, AAAI, ISWC, Interspeech, ICASSP

Job Description

  • Drive advanced research and engineering of Natural Language Processing (NLP) technologies
  • Apply research results to Bosch prototypes, products and services of information retrieval, question answering, conversational AI, and information extraction.
  • Working together with Bosch business units to integrate the resulting system/software into Bosch platform with high quality implementation
  • Summarize research findings in high-quality paper and/or patent submissions

Natural Language Processing Research Associate (KTP Associate) in Wilmslow, Cheshire, UK

  • Employer: University of Manchester
  • Title: Natural Language Processing Research Associate (KTP Associate)
  • Specialty: Natural Language Processing, Text Mining, Machine Learning
  • Location: Wilmslow, Cheshire, UK
  • Deadline: April 7, 2019
  • Date posted: March 7, 2019
  • Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk>

An exciting opportunity has arisen for an ambitious graduate who has the ability and confidence to undertake a Knowledge Transfer Partnership (KTP) project between the National Centre for Text Mining (NaCTeM), University of Manchester and Bott and Co.

Bott and Co is a multiple award-winning solicitors based in Wilmslow, near Manchester, with particular expertise in flight delay compensation, holiday sickness and road traffic accident claims.

The successful KTP associate will work with supervisors from both NaCTeM and Bott on a 30 month project, which has the overall aim of building a state-of-the-art Natural Language Processing (NLP) system for legal text mining and predictive modelling (PM).

The position will provide you with a unique opportunity to apply state-of-the-art methods in NLP and PM in the scope of legal analysis.

This post is funded through a Knowledge Transfer Partnership (KTP) award, a UK Government scheme intended to promote sustained and mutually beneficial relationships between universities and industry.


ESSENTIAL SKILLS

  • BSc and MSc degree in Computer Science or related areas
  • Specialist (PhD-level) knowledge in Natural Language Processing or extensive experience in the development of NLP/text analysis software
  • Experience in use of deep learning for NLP/text mining
  • Experience of machine learning (especially of context aware linear models for multi-task learning, and of active learning) for NLP/text mining
  • Experience of probabilistic inference, predictive modelling and decision making
  • Software development experience in Java or Python


LOCATION - Bott and Co, Wilmslow, Cheshire

SALARY - £32,236 to £39,609 per annum plus performance bonus and £5,000 personal development budget

DURATION - 30 months - starting ASAP

CLOSING DATE - 07/04/2019

FURTHER DETAILS AND APPLICATION FORM - https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16973


Postdoc position, KU Leuven

  • Employer: Department of Computer Science, KU Leuven
  • Title: Postdoctoral Researcher
  • Speciality: Representation learning in the context of natural language understanding
  • Location: Leuven, Belgium
  • Deadline: February 28, 2019
  • Date posted: February 13, 2019
  • Contact: sien.moens@cs.kuleuven.be


We offer a two-year postdoctoral position (extendable to four years) funded by the ERC (European Research Council) Advanced Grant CALCULUS “Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding” (http://calculus-project.eu). The position focuses on natural language understanding but gives possibilities to research topics in one or more of the following fields: machine learning (especially semi-supervised learning, transfer learning, incremental learning, deep learning and latent variable models), multimodal processing of language and visual data, learning the grounded meaning of language from various contexts in which language is used (e.g., physical, language and social), representation learning at the word, phrase, sentence or discourse level considering various contexts, learning commonsense knowledge about the world from multimodal data, multimodal grammar induction, and inference models for language understanding. The successful candidate will work on innovative natural language understanding research. He or she will be given the opportunity for personal development beyond research, for example by contributing to teaching (e.g., at the undergraduate and graduate levels). For an outstanding candidate there is the potential to grow into an assistant professorship.


KU Leuven ranks among the top 50 universities in THE World University Rankings 2019. The alumni of the LIIR lab have obtained outstanding positions in academics and industry (see https://liir.cs.kuleuven.be/people.php).


Responsibilities

  • Perform research in language understanding and novel machine learning paradigms in the frame of the CALCULUS project.
  • Carry out some teaching duties, which may include lectures/exercise sessions, the organization of student seminars, and the supervision of bachelor and master theses.
  • Help in the supervision of PhD researchers of the CALCULUS team.

Profile

  • You have (or are near completion of) a PhD in Computer Science (or a related field).
  • You have a motivated interest in fundamental research in language understanding and machine learning.
  • You have an outstanding track record of publications in relevant international peer-reviewed A ranked conferences and in relevant journals with high impact factor.
  • You are good at collaborating with and leading others.
  • You have a very good knowledge of English, both spoken and written.


Offer

  • We offer a 2 x two-year postdoctoral position, starting in the summer of 2019.
  • We offer a competitive wage and yearly budget to attend conferences and for short research stays.

Interested

Please contact Prof. dr. Marie-Francine Moens, tel.: +32 16 32 53 83, mail: sien.moens@kuleuven.be. Excellent candidates will be invited for an interview (possibly via Skype). The position will be closed when a valuable candidate is found.


Postdoc position, Masaryk University

  • Employer: Machine Learning and Data Processing Department, Faculty of Informatics, Masaryk University
  • Title: Postdoctoral Researcher
  • Speciality: natural language processing, knowledge representation and reasoning
  • Location: Brno, Czech Republic
  • Deadline: March 1, 2019
  • Date posted: January 15, 2019
  • Contact: Ales Horak: hales@fi.muni.cz, subject "Postdoc 2019"
  • Application link: https://www.muni.cz/en/about-us/careers/vacancies/43809

The Faculty of Informatics of Masaryk University (FI MU) in Brno, Czech Republic, invites applications for Post-doctoral positions in all areas of Computer Science. Brno, the second largest city in the Czech Republic, see https://www.gotobrno.cz/en/, is an attractive city for students and young researchers. The Faculty has a strong interest in attracting applications from abroad.

The postdoctoral positions are awarded for one year with an extension to the second year after a review. Gross salary is 50,000 CZK per month which, with an optional 10% bonus, sums to more than 25,500 EUR per year. Additional funds of 4,000 EUR per year will be available for travel and material expenses. Preferred start date of the contract is in June/July 2019, but other options can be negotiated without hassle.

Requirements

Candidates must have a PhD degree not older than 4 years at the time of application, from a university outside of the Czech and Slovak Republics. In case that the PhD defense is not yet finished, the candidate must also provide an official letter certifying that his/her PhD thesis has already been submitted for defense and outlining the expected schedule of the PhD defense. Candidates with a PhD degree from a Czech or Slovak university may also be considered if they prove at least two years of post-doctoral research experience abroad.

Evaluation

All candidates are expected to be fluent in English, while prior knowledge of Czech is not required. Candidates will be evaluated on the ground of their strong international research record, and preference will be given to those whose research areas match the research directions of the Faculty of Informatics; see http://www.fi.muni.cz/research/.

Application

Applications must be submitted electronically at the attached www address - the electronic application form (only reference letters, if not given directly to the applicant, may be sent by email). The applicants should provide the following documents with their application:

  • An academic CV, a list of publications, and a motivation letter.
  • A scanned copy of the PhD diploma, or a letter certifying submission of doctoral thesis for the defense.
  • One external reference letter, and one support letter (expression of interest) from a member of the academic staff of the Faculty of Informatics of Masaryk University. These letters, if cannot be attached by the applicant him/herself, may be sent to the e-mail address hales@fi.muni.cz.

All interested applicants are strongly advised to informally contact their expected host research groups at the Faculty of Informatics well ahead of submitting their application.

Contact

Assoc.Prof. Ales Horak, Head of the Department of Machine Learning and Data Processing

Submission of applications: https://www.muni.cz/en/about-us/careers/vacancies/43809

E-mail (for inquiries and reference letters): hales@fi.muni.cz, subject "Postdoc 2019"

Two postdoctoral positions, University of Pittsburgh

  • Employer: The Computational Social Dynamic Lab, University of Pittsburgh
  • Title: Postdoctoral Research Associate
  • Speciality: computational social science, NLP, machine learning.
  • Location: Pittsburgh, PA, USA
  • Deadline: January 15, or until position filled
  • Date posted: December 06, 2018
  • Contact: Yu-Ru Lin (email: <yuruliny@gmail.com> | web: http://yurulin.com | lab: https://picsolab.github.io/)

The Computational Social Dynamic (PICSO) Lab at the University of Pittsburgh is seeking two postdoctoral research associates for a computational social science project under the mentorship of Dr. Yu-Ru Lin and Dr. Rebecca Hwa. This highly interdisciplinary project aims to advance research methodology in revealing biases of different groups or cultures by analyzing social media data with cutting-edge methods of natural language processing and machine learning. The duration of the position is for one year, with the possibility of renewal. The compensation is competitive.

We welcome candidates who hold a PhD from a related background, including computational social science, computer science, computational linguistics, social psychology, sociology, political science, and applied mathematics. Particular priorities for hiring are:  (1) knowledge and experiences in distributed semantic representation, sentiment analysis, and text mining methods, ideally demonstrated by publications in established venues (ACL, EMNLP, NIPS, ICML, KDD, etc.); (2) demonstrated ability to work with social media data; (3) prior experiences with computational social sciences a plus.

For full consideration, candidates should submit the following materials electronically as a single PDF file to Dr. Yu-Ru Lin at <yuruliny@gmail.com>:

  1. A brief statement of interest describing your relevant background
  2. Current CV
  3. The names and contact information for two references (letters of recommendation will be solicited from finalists)
  4. Two publications or other writing samples

Please include "PostDoc Application 2019" in the email subject line.

Research Scientist Interns at Adobe Research, San Jose, California

  • Employer: Adobe Systems Incorporated
  • Title: Research Scientist Intern
  • Speciality: NLP, machine learning, dialog, and question answering.
  • Location: San Jose, CA, USA
  • Deadline: March 1, 2019
  • Date posted: December 06, 2018
  • Contact: bui@adobe.com

We are looking for Master and/or Ph.D. students with a strong background in NLP, machine learning, dialog, and/or question answering to work on our Creative Assistant project and Document Question Answering project. See our recent publications here for further details: https://sites.google.com/site/trungbuistanford/Home/publications

Assistant Professor Position at The University of Memphis

  • Employer: University of Memphis
  • Rank or Title: Assistant Professor
  • Specialty: ML/NLP with particular interest in educational technologies
  • Location: Memphis, Tennessee
  • Deadline: 1/7/19 but applications accepted until search completed
  • Date Posted: 11/28/18
  • Contact email: cconnor2@memphis.edu
  • Application link: [4]

The Department of Computer Science at the University of Memphis is seeking candidates for an Assistant Professor position beginning Fall 2019. The candidate’s research will be jointly supported by the Department of Computer Science and the Institute of Intelligent Systems (IIS). Focus area for this position include Machine Learning, Data Mining, and Big Data. Candidates whose research areas complement the language & discourse or learning focus area of the IIS are particularly encouraged to apply. Candidates from minority and underrepresented groups are highly encouraged to apply. Successful candidates are expected to develop externally sponsored interdisciplinary research programs, teach both undergraduate and graduate courses and provide academic advising to students at all levels.

Applicants should hold a PhD in Computer Science, or related discipline, and be committed to excellence in both research and teaching. Salary is highly competitive and dependent upon qualifications.

The Department of Computer Science ([5]) offers B.S., M.S., and Ph.D. programs as well as graduate certificates in Data Science and Information Assurance, and participates in an M.S. program in Bioinformatics (through the College of Arts and Sciences). The Department has been ranked 55th among CS departments with federally funded research. The Department regularly engages in large-scale multi-university collaborations across the nation. For example, CS faculty led the NIH-funded Big Data "Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K)" and the "Center for Information Assurance (CfIA)".

The Institute for Intelligent Systems consists of 54 faculty members across 14 departments including Communication Sciences and Disorders, Computer Science, Engineering, Education, Linguistics, Philosophy and Psychology. The IIS offers a graduate certificate in Cognitive Science, a minor in Cognitive Science, and is affiliated with BA and MS programs in other departments. The IIS receives $4-5 million in external awards per year from federal agencies such as NSF, IES, DoD, and NIH. Further information about the Institute for Intelligent Systems can be found at [6].

Known as America’s distribution hub, Memphis ranked as America’s 6th best city for jobs by Glassdoor in 2017. Memphis metropolitan area has a population of 1.3 million. It boasts a vibrant culture and has a pleasant climate with an average temperature of 63 degrees.

Screening of applications begins immediately. For full consideration, application materials should be received by January 7, 2019. However, applications will be accepted until the search is completed.

To apply, please visit [7]. Include a cover letter (please include a reference to this position as “CS-IIS”), curriculum vitae, statement of teaching philosophy, research statement, and three letters of recommendation. Direct all inquiries to Corinne O’Connor (cconnor2@memphis.edu).

A background check will be required for employment. The University of Memphis is an Equal Opportunity/Equal Access/Affirmative Action employer committed to achieving a diverse workforce.

Research Associate in Text Mining, University of Manchester, UK

  • Employer: University of Manchester
  • Title: Research Associate in Text Mining
  • Specialty: Text Mining
  • Location: Manchester, UK
  • Deadline: January 3, 2019
  • Date posted: November 27, 2018
  • Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk>

We invite applications for the Research Associate in Text Mining, which is tenable initially for 12 months starting as soon as possible. The post is part of the Discovering Safety Programme funded by Lloyds Register Foundation in collaboration with the Health and Safety Executive. The purpose of this project is to use a combination of text mining and machine learning methods for retrieving and organising textual information pertinent to incident and inspection reports for search and risk classification.

Post Objectives:

1. To develop a search system based on clustering methods.

2. To contribute to development of entity linking for the application.

3. To develop a classification system for risk assessment.

You should have a PhD or equivalent in Computer Science with emphasis in Text Mining and Machine Learning in particular clustering and classification. Experience in named-entity recognition, entity linking and terminology extraction will be desirable. Appropriate security clearance may be required for the successful applicant.

  • Salary : £32,236 - £39,609 per annum according to experienc
  • Hours Per week: Full Time
  • Contract Duration : 01 February 2019 until 31 January 2020

Further details: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16445

Research Fellow in Natural Language Processing and Text Mining, University of Manchester, UK

  • Employer: University of Manchester
  • Title: Research Fellow in Natural Language Processing and Text Mining
  • Specialty: Text Mining
  • Location: Manchester, UK
  • Deadline: January 3, 2019
  • Date posted: November 23, 2018
  • Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk>

We invite applications for the above position to increase the University of Manchester's capacity in Natural Language Processing and Text Mining, which is available immediately for an initial 5 year period leading to an open-ended academic position.

The Research Fellow will further strengthen the research profile of the text mining research group at the University of Manchester and the National Centre for Text Mining. We are looking for an outstanding candidate that has a vision for making a significant impact on natural language processing, text mining research and its applications. The Fellow will be part of the Discovering Safety Programme project funded by Lloyds Register Foundation in collaboration with the Health and Safety Executive. This post is one of the key first posts to be appointed in the Thomas Ashton Institute for Risk and Regulatory Research.

You will join the vibrant research environment of the Text Mining research group at the School of Computer Science and will be a member of the National Centre for Text Mining which is developing cross cutting and innovative approaches for text mining applications using NLP and machine learning.

As a member of the Thomas Ashton Institute, the Fellow will join, and help establish, a multidisciplinary centre of excellence and expertise, which offers an exciting opportunity for ground breaking and excellent research to inform both government regulatory regimes and industry practice.

  • Salary : £40,792 to £50,132 per annum dependent upon experience
  • Hours Per week: Full Time
  • Contract Duration : Starting Immediately until 31 December 2023

Further details: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16448

Associate Research Scientist, UKP Lab, TU Darmstadt

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

Associate Research Scientist
(PhD-level; for an initial term of two years)

to strengthen the group’s profile in the areas of Interactive Text Analysis and Natural Language Processing Tools. The UKP Lab is an internationally recognized research institute with about 35 team members. We work on various aspects of Natural Language Processing (NLP), with a rapidly developing focus on Interactive Machine Learning. Besides, we provide a range of high-quality open source software packages for interactive and automatic text analysis to research and industry communities and collaborate with both academic and industrial partners.

We ask for applications from candidates in Computer Science with a specialization in Semantic Web Technologies and either Information Retrieval or Natural Language Processing, preferably with expertise in research and development projects, and strong communication skills in English and German.

The successful applicant will work on research and development for interactive text annotation by end-users (researchers, analysts, etc.). This includes neural network-based methods for knowledge graph construction and completion, interactive sequence labeling recommender systems, or semantic information retrieval. We integrate the results in a real-life collaborative text annotation software for large-scale interactive corpus analysis.

Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP and/or ML) systems (frontend and backend), in applying NLP-related Machine Learning-based methods (e.g. learning-to-rank, clustering, etc.), experience with information retrieval systems (e.g. Lucene, Solr, ElasticSearch) and relational databases (SQL), semantic web technologies (e.g. RDF, OWL, SPARQL), and strong programming skills especially in Java. Experience with neural network architectures (e.g. knowledge-base embeddings) and demonstrable engagement in open- source projects are a strong plus.

UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research focus "Data Science” and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals. In 2018, Darmstadt has achieved the first place in the category Cities of the Future in a ranking of German cities.

Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).

Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please apply under https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/ by December 15, 2018. The positions are open until filled. Later applications may be considered if the position is still open.

Associate Research Scientist, UKP Lab, TU Darmstadt

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

Associate Research Scientist
(PhD- or (Senior-)PostDoc level; for an initial term of two years)

The UKP Lab is an internationally recognized research institute with about 35 team members. We work on various aspects of Natural Language Processing (NLP), with an emphasis on semantic text analysis and generation, argument mining, and interactive machine learning. Besides, we have a strong profile in deep learning for NLP, construction of large-scale benchmarks, or knowledge graphs. We collaborate with a wide range of both academic and industrial partners.

We are looking for candidates in Computer Science with a specialization in Natural Language Processing, preferably with expertise in research and development projects, prior publication experience, and strong communication skills. The research topics of the position may include: NLP in low-research settings, argument mining and retrieval, multimodal content processing, privacy-enhanced NLP as well as machine learning for NLP (deep reinforcement learning, neural network architectures). The successful applicant will work on research and development as part of a team in one of the areas above. We disseminate the results in top venues of the field and as free research software and datasets. The lab offers highly attractive options for personal growth and career development at all levels of the scientific career. Upon interest, additional qualifications in teaching and project management can be acquired.

UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research focus "Data Science” and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals. In 2018, Darmstadt has achieved the first place in the category Cities of the Future in a ranking of German cities.

Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).

Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please apply under https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/ by December 15, 2018. The positions are open until filled. Later applications may be considered if the position is still open.

Assistant Professor, Department of Linguistics and Translation, University of Montreal

  • Employer: Department of Linguistics and Translation, University of Montreal
  • Title: Assistant Professor (tenure-track)
  • Specialty: Computational linguistics
  • Location: Montreal, Canada
  • Deadline: December 13, 2018
  • Date posted: November 10, 2018
  • Contact: Mireille Tremblay <mireille.tremblay.4@umontreal.ca > and https://ling-trad.umontreal.ca

The Département de linguistique et de traduction is seeking applications for a full-time tenure-track position at the rank of Assistant Professor in computational linguistics/natural language processing.

Responsibilities

The appointed candidate will be expected to teach at all three levels of the curriculum, supervise graduate students, engage in ongoing research and publication, and contribute to the academic life and reputation of the University. This person will play an important role in the development of the “Computational Linguistics” branch of our curriculum and in establishing cross-disciplinary collaborations within and outside of the University.

Requirements

  • Ph.D. in linguistics, computer science, or a related field.
  • Education in both linguistics and computer science, with a strong background in core linguistics.
  • Demonstrated interest in using computational techniques in the study of language.
  • Ability to teach in at least one of the core domains of linguistics.
  • Excellent publication track record in computational linguistics.
  • University teaching experience.
  • Sufficient knowledge of written and spoken French.

Deadline: until December 13, 2018 inclusively

Treatment: Université de Montréal offers competitive salaries and a full range of benefits.

Starting date: On or after August 1st, 2019

Application

The application must include the following documents:

  • a cover letter
  • a curriculum vitæ
  • copies of recent publications and research

Three letters of recommendation are also to be sent directly to the department chair by the referees.

Application and letters of recommendation must be sent to the chair of the Département de linguistique et de traduction at the following address:

Mireille Tremblay, directrice
Département de linguistique et de traduction
Faculté des arts et des sciences
Université de Montréal
C.P. 6128, succursale Centre-ville
Montréal (QC) H3C 3J7
Canada

Application and letters of recommendation may also be sent by email at the following address: mireille.tremblay.4@umontreal.ca

For more information about the Department, please consult its website at http://ling-trad.umontreal.ca

Université de Montréal is a Québec university with an international reputation. French is the language of instruction. To renew its teaching faculty, the University is intensively recruiting the world’s best specialists. In accordance with the institution’s language policy, Université de Montréal provides support for newly-recruited faculty to attain proficiency in French.

The Université de Montréal application process allows all regular professors in the Department to have access to all documents unless the applicant explicitly states in her or his cover letter that access to the application should be limited to the selection committee. This restriction on accessibility will be lifted if the applicant is invited for an interview.

Through its Equal Access Employment Program, Université de Montréal invites women, Aboriginal people, visible and ethnical minorities, as well as persons with disabilities to apply. During the recruitment process, our selection tools will be adapted to meet the needs of people with disabilities who request it. Be assured of the confidentiality of this information.

Université de Montréal is committed to the inclusion and the diversity of its staff and also encourages people of all sexual and gender identities to apply.

We invite all qualified candidates to apply at UdeM. However, in accordance with immigration requirements in Canada, please note that priority will be given to Canadian citizens and permanent residents.


Software Engineer for Text Mining Applications at the University of Manchester

  • Employer: National Centre for Text Mining, School of Computer Science, University of Manchester
  • Title: Software Engineer
  • Specialty: Text Mining
  • Location: Manchester, UK
  • Deadline: November 25, 2018
  • Date posted: October 25, 2018
  • Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk>

Applications are invited for a Software Engineer post (full time) for a period of 5 years

The successful candidate will be part of the National Centre for Text Mining (http://www.nactem.ac.uk/) which is hosted by the School of Computer Science, joining a strong and dynamic team in text mining. The National Centre for Text Mining provides next-generation text mining services to the community. We use natural language processing techniques to build advanced search systems in a number of domains. We are seeking a self-motivated, creative and experienced software engineer (must have substantive post graduation experience) to enhance our team expertise particularly in the areas of wrapping text mining analysis workflows, software development for search engines bringing the benefits of text mining to end users, Web services, integrating text mining with knowledge bases, cloud deployment of services and advanced user interfaces.

Essential skills and experience include: Linux/unix, extensive experience of software design and development gained in a professional software development environment, experience of producing distributed solutions and of working with large datasets, Java or C++ with XML technologies, REST/SOAP Web services, knowledge of cloud/cluster computing/SaaS/PaaS, Maven.

  • Salary : £40,792 to £50,132 per annum dependent upon experience
  • Hours Per week: Full Time
  • Contract Duration : Starting 1 January 2019 for 5 years

Further details: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16308


Assistant Professor, Department of Linguistics, University of Florida

  • Employer: Department of Linguistics, University of Florida
  • Title: Tenure-track Assistant Professor
  • Specialty: computational language science
  • Location: Gainesville, FL 32601
  • Deadline: November 18, 2018
  • Date posted: October 18, 2018
  • Contact: Stefanie Wulff <swulff@ufl.edu> and https://apply.interfolio.com/56557

The University of Florida invites applications for a tenure-track appointment in computational language science at the rank of assistant professor, effective August 16, 2019. This is a 9-month position. Applicants are expected to have a Ph.D. in linguistics, computer science, or a closely-related field. Candidates should have an active research agenda studying language from a computational perspective. Specialization is open, including but not limited to sociolinguistics, neuro/psycholinguistics, corpus linguistics, and/or language documentation. UF Linguistics seeks to train the next generation of linguists who are comfortable integrating and evaluating computational approaches in their research. To this end, ability to teach computationally-oriented courses is required. Candidates must hold the Ph.D. by the starting date.

The successful candidate will be expected to 1) maintain an active research agenda, 2) pursue external research funding, 3) teach two courses per semester at the undergraduate and/or graduate level, 4) provide service to the department, the university, and the profession, and 5) seek collaborations within the department as well as with other units on campus such as the UF Data Science and Information Technology Center, the UF Informatics Institute, or the McKnight Brain Institute.

The Department is committed to creating an environment that affirms diversity and inclusion across a variety of dimensions, including ability, class, ethnicity/race, religion and/or cultural background, gender identity and expression. We particularly welcome applicants who can contribute to such an environment through their scholarship, teaching, mentoring, and professional service. The university and greater Gainesville community enjoy a diversity of cultural events, restaurants, year-round outdoor recreational activities, and social opportunities

Salary is competitive, commensurate with qualifications and experience, and includes a full benefits package.

The Linguistics Department at the University of Florida is a vibrant and congenial unit consisting of 11 full-time faculty and 15 affiliated faculty in the departments of Anthropology; Languages, Literatures, and Cultures; Spanish and Portuguese; and the Dial Center for Written & Oral Communication. We offer a B.A., M.A. and Ph.D. in Linguistics, as well as an undergraduate minor and undergraduate certificate in TESL and a graduate certificate in Second Language Acquisition and Teaching. We have faculty expertise in a wide range of linguistic subfields, and particular strengths in the areas of bilingualism, language documentation, psycholinguistics, sociolinguistics, and African linguistics. Please see our website, lin.ufl.edu, for more information about the department.

For full consideration, applications must be submitted online at https://apply.interfolio.com/56557 and must include: (1) a brief cover letter, (2) a statement of teaching and research interests, (3) a CV, (4) 1-3 sample publications, (5) the names and email addresses for three references, and (6) representative teaching evaluations if available. After initial review, letters of recommendation will be requested for selected applicants. Review of applications will begin on 18 November 2018 and will continue until the position is filled.

All candidates for employment are subject to a pre-employment screening which includes a review of criminal records, reference checks, and verification of education.

The final candidate will be required to provide an official transcript to the department upon hire. A transcript will not be considered "official" if a designation of "Issued to Student" is visible. Degrees earned from an educational institution outside of the United States require evaluation by a professional credentialing service provider approved by the National Association of Credential Evaluation Services (NACES), which can be found at http://www.naces.org/.

The University of Florida is an Equal Opportunity Employer dedicated to building a broadly diverse and inclusive faculty and staff. The University of Florida invites all qualified applicants, including minorities, women, veterans, and individuals with disabilities to apply. The University of Florida is a public institution and subject to all requirements under Florida Sunshine and Public Record laws.

Postdoctoral Researcher, Cognitive AI Lab, University of Arizona

  • Employer: School of Information, University of Arizona
  • Title: Postdoctoral Research Associate
  • Specialty: natural language processing
  • Location: Tucson, AZ, USA
  • Deadline: Open until filled
  • Date posted: October 15, 2018
  • Contact: Peter Jansen <pajansen@email.arizona.edu>

Postdoctoral Research Associate I
https://uacareers.com/postings/31213

Position Summary
The Cognitive Artificial Intelligence Laboratory ( http://www.cognitiveai.org ) in the School of Information at the University of Arizona invites applications for a Postdoctoral Research Associate for projects specializing in natural language processing and explanation-centered inference.

Natural language processing systems are steadily increasing performance on inference tasks like question answering, but few systems are able to provide explanations describing why their answers are correct. These explanations are critical in domains like science or medicine, where user trust is paramount and the cost of making errors is high. Our work has shown that one of the main barriers to increasing inference and explanation capability is the ability to combine information – for example, elementary science questions generally require combining between 6 and 12 different facts to answer and explain, but state-of-the-art systems generally struggle integrating more than two facts together. The successful candidate will combine novel methods in data collection, annotation, representation, and algorithmic development to exceed this limitation in combining information, and apply these methods to answering and explaining science questions.

A talk on our recent work in this area is available here: https://www.youtube.com/watch?v=EneqL2sr6cQ

Minimum Qualifications

  • A Ph.D. in Computer Science, Information Science, Computational Linguistics, or a related field.
  • Demonstrated interest in natural language processing or machine learning techniques.
  • Excellent verbal and written communication skills

Duties and Responsibilities

  • Engage in innovative natural language processing research
  • Write and publish scientific articles describing methods and findings in high-quality venues (e.g. ACL, EMNLP, NAACL, etc.)
  • Assist in mentoring graduate and undergraduate students, and the management of ongoing projects
  • Support writing grant proposals for external funding opportunities
  • Serve as a collaborative member of a team of interdisciplinary researchers

Preferred Qualifications

  • Knowledge of computational approaches to semantic knowledge representation, graph-based inference, and/or rule-based systems
  • Strong scholarly writing skills and publication record

Full Posting/To Apply
https://uacareers.com/postings/31213

Temporary lecturer, Department of Linguistics, University of California, Santa Barbara

  • Employer: Department of Linguistics, University of California, Santa Barbara
  • Title: Lecturer
  • Specialty: computational linguistics and/or natural language processing and general linguistics
  • Location: Santa Barbara, CA 93106
  • Deadline: October 24, 2018
  • Date posted: September 27, 2018
  • Contact: https://recruit.ap.ucsb.edu/apply/JPF01317

The Department of Linguistics at the University of California, Santa Barbara invites applications for a qualified temporary Lecturer to teach course(s) in computational linguistics and potentially general linguistics. To learn more about the department, see: http://www.linguistics.ucsb.edu/

The Lecturer will teach an advanced undergraduate course in computational linguistics in the Winter 2019 or Spring 2019 quarter. The successful candidate may also have the opportunity to teach other courses that support the department’s undergraduate programs, including classes currently listed in the UCSB general catalog and/or special-topic courses proposed by the applicant; these courses may be offered in Winter 2019 or Spring 2019.

Applicants must possess a Master’s Degree in Linguistics and have at least one year teaching college-level linguistics courses. A Ph.D. in Linguistics is preferred but not required. The department is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.

To apply, please go to the following link: https://recruit.ap.ucsb.edu/apply/JPF01317. Applicants should submit a curriculum vitae and a cover letter stating their qualifications for teaching computational linguistics as well as any additional courses they may be interested in teaching. Applicants should also provide contact information for three references. To ensure full consideration, all application materials should be received by 10/24/18; however, the position is open until filled.

The University of California is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Assistant Professor, Department of Linguistics, University of California, Santa Barbara

  • Employer: Department of Linguistics, University of California, Santa Barbara
  • Title: Assistant Professor
  • Specialty: computational linguistics and/or natural language processing
  • Location: Santa Barbara, CA 93106
  • Deadline: November 9, 2018
  • Date posted: September 27, 2018
  • Contact: https://recruit.ap.ucsb.edu/apply/JPF01310 and complingsearch@linguistics.ucsb.edu

The Linguistics Department of the University of California, Santa Barbara seeks to hire a linguist who is a specialist in computational linguistics and/or natural language processing. The appointment will be a tenure-track position at the Assistant Professor level, effective July 1, 2019.

The successful candidate will have an active research program in computational linguistics and/or natural language processing and will have a record of participation in the computational linguistics/NLP community. Proven expertise in machine learning including word embeddings/vector space semantics is required, as is expertise in using computational linguistics methods to address theoretical and/or applied questions. Capacity to engage with the distinctive theoretical orientation of the department is expected. We welcome applicants with the ability to contribute to departmental foci, such as corpus linguistics, language and cognition, language acquisition, and/or less studied languages. We also encourage applicants who have the potential to interact with colleagues and students across disciplinary boundaries at UCSB.

The successful candidate will demonstrate commitment to and ability in graduate and undergraduate teaching and will be expected to teach a range of graduate and undergraduate courses in computational linguistics, including those with relevance to industry, as well as to contribute to the department’s undergraduate major with an emphasis in Language and Speech Technologies. For more information on the department, see www.linguistics.ucsb.edu.

The minimum requirement to be considered as an applicant is the completion of all requirements for a Ph.D. in linguistics or a closely-related field except the dissertation (or equivalent) at the time of application. A Ph.D. in linguistics or a closely-related field is expected by the time of appointment. Review of applications will begin after Friday, November 9, 2018. The position will remain open until filled.

Applicants must complete the online form at https://recruit.ap.ucsb.edu/apply/JPF01310 and must submit online the following in PDF format: letter of application, statement of research interests, teaching statement, curriculum vitae, and 2 writing samples. Applicants are also encouraged to submit an optional statement on contributions to diversity.

Applicants should request 3-5 letters of reference to be sent directly to https://recruit.ap.ucsb.edu/reference. Inquiries may be addressed to the Search Committee at complingsearch@linguistics.ucsb.edu. Initial screening of selected applicants will be conducted via Zoom. Our department has a genuine commitment to diversity, and is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.

The University of California is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Postdoctoral Fellow, Quantitative Criticism Lab, University of Texas at Austin

The Quantitative Criticism Lab (QCL; https://www.qcrit.org), a research group developing cross-disciplinary approaches to the study of literature and culture, invites applications for a full-time postdoctoral fellowship. The duration of the fellowship is 18 months, from January 2, 2019 to June 30, 2020. The field of specialization is open, but expertise in computer programming and statistical analysis is essential, as is a deep interest in the study of literature. QCL’s physical lab space is based at The University of Texas at Austin; residence in Austin during the fellowship period is preferred but not required. The fellow will have no teaching responsibilities. The position is funded by a Digital Extension Grant from the American Council of Learned Societies (ACLS).

The ACLS-funded project will produce a web-based suite of tools for traditionally-trained humanists to analyze literary texts in a quantitative manner. The tools are designed with an important class of literary problems in mind, exemplified by the identification of verbal parallels and, at a larger scale, by the individuating of entire works within generic traditions. We take two main approaches: sequence alignment for the detection of verbal resemblance, and stylometry augmented by machine learning for the profiling of texts and corpora. The tools are expected both to enhance traditional modes of literary criticism and to enable novel quantitative analyses of the cultural evolution of literature.

The postdoctoral fellow’s primary responsibilities will be to lead development of these tools and to participate in other aspects of QCL’s research program according to background and interests. The work will involve coding, research design, data analysis, literary criticism, and scholarly writing for diverse venues, as well as various organizational duties related to workshops and conferences. The postdoctoral fellow will work under the supervision of Pramit Chaudhuri (UT Austin) and Joseph Dexter (Dartmouth College), the co-directors of QCL, and will collaborate with a diverse array of scholars, in both academia and industry, affiliated with QCL. In addition, the fellow will be expected to play a major role in mentoring the numerous graduate, undergraduate, and high school students who conduct research with QCL.

A Ph.D. in a computational, statistical, linguistic, or literary field is required. Possible disciplines include (but are not limited to) anthropology, applied mathematics, bioinformatics, classics, comparative literature, computer science, English, evolutionary biology, linguistics, and statistics. Prior experience with any of the following areas is highly desirable but not required: computational linguistics, cultural evolution, digital humanities, literary criticism of a premodern or non-Anglophone tradition (especially Latin or Ancient Greek), machine learning, and natural language processing. By the start date of the position, applicants should either have the Ph.D. in hand or be able to provide certification from their home institution that all degree requirements have been fulfilled. Applicants must have received the Ph.D. within the last three years.

For full consideration, applicants should submit the following materials by October 15, 2018:

  1. CV;
  2. Cover letter;
  3. Short (2-4 page) summary of past and current research interests, giving particular attention to any computational work;
  4. Writing sample of no more than 40 pages (e.g., article or dissertation chapter).

In addition, applicants should arrange to have three letters of recommendation forwarded by the deadline. Please submit your CV and cover letter on the UT Jobs website: https://utdirect.utexas.edu/apps/hr/jobs/nlogon/180823010712. Please submit the additional materials via email to vnoya@austin.utexas.edu. Questions can be directed to Vanessa Noya at the same address.

The salary will be $48,000 per year, plus benefits.

The successful candidate must be able to begin work in this position by January 2, 2019.

A criminal history background check will be required for finalist(s) under consideration for this position.

The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.

If hired, you will be required to complete the federal Employment Eligibility Verification form, I-9. You will be required to present acceptable, original documents (https://hr.utexas.edu/current/services/employment-eligibility-verification-i9-docs) to prove your identity and authorization to work in the United States. Information from the documents will be submitted to the federal E-Verify system for verification. Documents must be presented no later than the third day of employment. Failure to do so will result in dismissal.

UT Austin is a Tobacco-free Campus (http://tobaccofree.utexas.edu/).

Associate Research Scientist, UKP Lab, TU Darmstadt

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

Associate Research Scientist
(PostDoc- or PhD-level; for an initial term of two years)

This position should further strengthen and develop the profile of the lab in natural language processing (NLP) and related topics such as machine learning, multimodal content analysis, information retrieval, or novel applications of NLP to social sciences and humanities.

Possible areas of research include, but are not limited to:

  • interactive clustering and machine learning to extract sets of textual snippets according to multiple criteria, e.g. high-quality and diverse examples illustrating a lexical entry’s usage;
  • NLP for low-resource languages, e.g. analyzing discourse-level argumentation in Georgian;
  • interactive sequence labeling to support claim validation by experts, e.g. for extracting evidence from corpora;
  • joint text and image processing for content classification in social media, e.g. identifying bias;
  • analyzing and generating creative language, such as humor, metaphor, or other rhetorical means.

The lab has a strong profile in the above areas, which features robust semantic analysis and textual inference, multimodal content analysis and summarization, and applications of NLP including novel benchmarks and problem definitions. It currently develops a new focus on interactive machine learning and chatbots and conversational agents. The lab closely cooperates with machine learning, computer vision, and data management groups of the Computer Science department. It has a strong industrial network and works together with social sciences and humanities on real-life research problems.

We are looking to attract highly qualified candidates with an outstanding degree in NLP, machine learning, or a related field of Computer Science. The candidates should preferably have research and teaching experience and strong communication skills in English and German (optional). Together with the candidate, we work out an individual career development plan and identify the relevant opportunities for the professional and personal growth within the activities of the lab.

The research environment is excellent. The Department of Computer Science of the TU Darmstadt is regularly one of the top ranked ones among the German universities. Its unique Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG and the BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasize NLP, machine learning and text mining.  UKP Lab is a very dynamic research group committed to high-profile research, cooperative work style and close interaction of team members.

Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of ideally three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by September 30th, 2018: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.

Tenure-track and tenure-eligible investigators at the National Library of Medicine, Bethesda, Maryland

  • Employer: National Library of Medicine
  • Title: Tenure-track and tenure-eligible investigators
  • Specialty: Natural Language Processing
  • Location: Bethesda, MD, USA
  • Deadline: Applications will be accepted until the position is filled.
  • Date posted: August 15, 2018
  • Contact: Dr. Andy Baxevanis, the Search Chair, <andy@mail.nih.gov>

The National Library of Medicine is currently recruiting for both tenure-track and tenure-eligible investigators in data science, biomedical informatics, and computational biology. Individuals with significant experience in the use of statistical, machine learning, optimization and advanced mathematical methodologies as applied to biomedical and health science are encouraged to apply. Additional details are available by following the links below.

https://www.nlm.nih.gov/careers/jobopenings.html https://www.nlm.nih.gov/careers/jobopening_ncbi_01_20180813.html https://www.nlm.nih.gov/careers/jobopening_ncbi_02_20180813.html


Question-Answering Research Internship at Adobe Research, San Jose, California

  • Employer: Adobe Research
  • Title: Research Scientist Intern
  • Speciality: Question-answering
  • Location: San Jose, CA, USA
  • Deadline: Applications will be accepted until the position is filled.
  • Date posted: July 3, 2018
  • Contact: Franck Dernoncourt <dernonco@adobe.com>

We are looking for a PhD student with background in question-answering for a late summer or autumn, ~13-week internship (starting date and length are flexible). We strongly encourage our interns to publish their work to NLP/ML conferences/journals, and as a result we prefer candidates with a strong publication record. International PhD students are welcome to apply. Highly competitive salary. To apply, please send me an email with your CV (e.g., PDF or LinkedIn) as well as the list of your publications (e.g., PDF or link to your Google Scholar profile).

Postdoctoral position in natural language understanding, KU Leuven, Belgium

  • Employer: KU Leuven, Belgium
  • Title: Postdoctoral researcher
  • Specialty: Natural language understanding, machine learning
  • Location: Leuven, Belgium
  • Deadline: July 31, 2018
  • Date posted: June 18, 2018
  • Contact: sien.moens@cs.kuleuven.be

We offer a two-year postdoctoral position (extendable to four years) funded by the ERC (European Research Council) Advanced Grant CALCULUS “Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding” (http://calculus-project.eu). The principal investigator is Prof. Sien Moens. CALCULUS focuses on learning effective anticipatory representations of events and their narrative structures that are trained on language and visual data. The machine learning methods on which CALCULUS will build belong to the family of latent variable models where it will rely on Bayesian probabilistic models and neural networks as starting points. CALCULUS focuses on settings with limited training data that are manually annotated and especially aims at developing novel machine learning paradigms for natural language understanding. CALCULUS also evaluates the inference potential of the anticipatory representations in situations not seen in the training data and for inferring spatial, temporal and causal information in metric real world spaces. The best models for language understanding will be integrated in a demonstrator that translates language to events happening in a 3-D virtual world.

The successful candidate will have an opportunity to work on innovative natural language understanding research such as grounding language meaning into visual perception and translating narrative language into visual events. He or she will be given the opportunity for personal development beyond research, for example by contributing to teaching (e.g., at the undergraduate and graduate levels). For an outstanding candidate there is the potential to grow into an assistant professorship.


Responsibilities

  • Perform own research in language understanding and novel machine learning paradigms in the frame of the CALCULUS project.
  • Carry out some teaching duties, which may include lectures/exercise sessions, the organisation of student seminars, and the supervision of bachelor and master theses. 
  • Help in the supervision of PhD researchers of the CALCULUS team.

Prerequisites

  • You have (or are near completion of) a PhD in Computer Science (or a related field).
  • You have a motivated interest in fundamental research in language understanding and machine learning.
  • You are not afraid of creative and original ideas and solutions.
  • You have an outstanding track record of publications in relevant international peer-reviewed A ranked conferences and in relevant journals with high impact factor.
  • You are good at collaborating with and leading others.
  • You work proactively and independently and have good communication skills.
  • You have a very good knowledge of English, both spoken and written.
  • You are highly motivated, ambitious and result-oriented.

  Offer

  • We offer a 2 x 2-year postdoctoral position, starting in September 2018 (negotiable).
  • We offer a competitive wage and yearly budget to attend conferences and for short research stays.

  Interested If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).

The research team

The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.

The university

KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!

Postdoctoral position in multilingual text mining, KU Leuven, Belgium

  • Employer: KU Leuven, Belgium
  • Title: Postdoctoral researcher
  • Specialty: Text mining, machine learning
  • Location: Leuven, Belgium
  • Deadline: July 31, 2018
  • Date posted: June 18, 2018
  • Contact: sien.moens@cs.kuleuven.be

We offer a two-year postdoctoral position funded by the EU ITEA3 project PAPUD "Profiling and Analysis Platform Using Deep Learning” (https://itea3.org/project/papud.html). The principal investigator is Prof. Sien Moens. The scope of the project is to build a universal model for data analytics using deep learning in order to help today’s businesses to make sense out of data. The postdoctoral position focuses on multilingual text mining and more specifically on interlingual content representations and methods of transfer learning with applications in multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. The candidate will perform cutting-edge artificial intelligence research in the context of a European consortium composed of renowned academic and industrial partners.

  Responsibilities

  • Design and develop machine learning methods for multilingual text mining.
  • Carry out some teaching duties, which may include lectures/exercise sessions, the organization of student seminars, and the supervision of bachelor or master theses. 

  Prerequisites

  • You have (or are near completion of) a PhD in Computer Science (or a related field).
  • You have a motivated interest in and knowledge of text mining and machine learning, including probabilistic graphical models and deep learning. 
  • You have a solid track record of publications in relevant international peer-reviewed A ranked conferences and journals.
  • You have a profound interest in collaborating with the industry on applications of text mining and willing to contribute to a deep learning text analytics platform.
  • You have a very good knowledge of English, both spoken and written.
  • You are highly motivated, ambitious and result-oriented.

  Offer

  • We offer a two-year postdoctoral position, starting in September 2018 (negotiable).
  • We offer a competitive wage and yearly budget to attend conferences.

  Interested

If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).

The research team

The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.

The university

KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!

PhD positions in DFG Graduate School AIPHES, TU Darmstadt

The Research Training Group “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES), which has been established in 2015 at Technische Universität Darmstadt and at Ruprecht Karls University Heidelberg is filling two positions for three years, starting as soon as possible, located in Darmstadt and associated with UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled. The positions provide the opportunity to obtain a doctoral degree with an emphasis in natural language processing tasks such as structured summaries of complex contents, abstractive summarization, or a related area. Applicants should be willing to work on cross-lingual, cross-modality and domain-independent methods. Prior experience in transfer learning, multi-task learning, adversarial learning, deep reinforcement learning or related methods is a plus.

The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, computer vision, and data and information management will be developed. AIPHES investigates a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore benefit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.

AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS). AIPHES strives to publish its results at leading scientific conferences and is actively supporting its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.

Prerequisites

We are looking for exceptionally qualified candidates with a degree in Computer Science, Machine Learning, NLP, or a related study program. We expect the ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Prior experience in scientific work is a plus. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.

The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. UKP Lab is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members. Its BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, machine learning and text mining. The large-scale argument mining project allows searching large document collections in response to a user-defined topic: neural networks determine relevant pro and con arguments in real-time, and represent them in a concise summary.

Applications should include a motivational letter that refers to one of the planned research areas of AIPHES, a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by June, 27th, 2018:

https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/

In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.

Postdoc position: Bocconi University, Milan

  • Employer: Bocconi University
  • Title: Postdoctoral Researcher
  • Location: Milan, Italy
  • Deadline: June 22nd, 2018, 5 p.m.


  • Starting date: as early as possible, but no later than September 2018
  • Duration: 1 year


  • Date Posted: June 18, 2018
  • Contact: Paola Cillo (paola.cillo@unibocconi.it)
  • URL: https://bit.ly/2JW2tKZ (select the Gucci Lab call)

Gucci Research Lab (GRL) is a unique partnership between Bocconi University and Gucci to identify and study the trends that define the way in which organizations are evolving. This position is part of a larger project by the Gucci Lab at Bocconi on the effects of a change in a firm’s leadership positions on the firm’s culture and its performance. Part of the project involves the textual analysis of internal documents (e.g., emails), before and after the leadership change. To provide an example, textual analysis of these documents will be conducted to identify power relationships within the organization and study how they evolved over time.

REQUIREMENTS/QUALIFICATIONS



The successful candidate will work actively on novel directions in deep learning, multi-task learning, and neural networks.

The candidate is expected to have:

  • a Ph.D. or equivalent in Computer Science, Computational Linguistics/NLP,
Mathematics or related fields.
  • Good programming skills in Python.
  • Fluent English. Knowledge of other languages is more than welcome.
 Knowledge of Italian is NOT a requirement.
  • Knowledge of current neural network models, especially Word2Vec and Doc2Vec, and tools for neural networks (e.g. Tensorflow, Keras, PyTorch, etc.).
  • Publications in top-tier venues in the field of Computational Linguistics.
  • Experience in Ph.D. student supervision is a plus.
  • Salary: 43,310.50 euros per annum

HOW TO APPLY



The application must be sent to Faculty and Research Division of Bocconi University (addressing the Rector) just via email at recruiting_ricerca@unibocconi.it You can find more information about the project and call here: https://bit.ly/2t1DnAO

Postdocs: Johns Hopkins University

  • Employer: Johns Hopkins University
  • Title: Postdoctoral Researcher
  • Location: Baltimore, MD
  • Deadline: Applications will be accepted until positions are filled
  • Date Posted: June 6, 2018
  • Contact: clspsearch@clsp.jhu.edu
  • URL: https://www.clsp.jhu.edu/employment-opportunities/


The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech, natural language processing and machine learning. Applicants must have a Ph.D. in a relevant discipline and a strong research record.

The center has a number of postdoctoral positions available. A single application will be considered for all open positions (except for one position as noted below). You need not indicate a specific position, but you may include a strong preference in an optional cover letter.

Example topics include:

  • Cross-lingual Information Retrieval
  • Trend Detection in Social Media
  • Social Media and Mental Health
  • Analysis of Clinical Medical Text
  • Broadly Multilingual Learning of Morphology and Low-Resource Machine Translation
  • NLP and Machine Learning for Clinical Data Analysis

Johns Hopkins University is a private university located in Baltimore, Maryland. The campus provides easy access to a number of affordable and vibrant neighborhoods and waterfront dining options. Hopkins is also connected to Washington DC (40 mins), Philadelphia (1.5 hours) and New York city (2.5 hours) via direct trains and buses.

CLSP is one of the world’s largest academic centers focused on speech and language. CLSP is home to a dozen faculty members, half a dozen postdocs, and over 60 graduate students. It has a history of placing students in top academic and industry positions, with a large network of alumni at Google, Amazon, Microsoft Research, Bloomberg, IBM Research, Facebook, Twitter, Nuance, BBN, and numerous startups.

Applicants are not required to be to US citizens or permanent residents.

Questions about specific projects should be directed to the contact information associated with the project. General inquiries may be sent to clspsearch@clsp.jhu.edu.

Details and application information: http://www.clsp.jhu.edu/employment-opportunities/


Research Fellow in Software Engineering with a Focus on Natural Language Processing at University of Tartu, Estonia

  • Employer: University of Tartu, Institute of Computer Science, Software Engineering group
  • Title: Research Fellow
  • Speciality: Software engineering, machine learning, natural language processing
  • Location: Tartu, Estonia
  • Deadline: June 4, 2018
  • Date posted: May 21, 2018
  • Contact: Dietmar Pfahl, Kairit Sirts (<firstname>.<lastname>@ut.ee)

Postdoctoral position
Applications are invited for a position of Research Fellow at the Software Engineering and Information Systems Research Group, Institute of Computer Science, University of Tartu. The institute is the leading Computer Science department in the Baltics and is one of the top-2 in Central and Eastern European universities according to the field-specific Times Higher Education Ranking 2017. The Software Engineering and Information Systems group conducts research in the fields of data-driven software engineering decision support, business process management, and secure information systems design. The group is composed of 25 members, including 12 PhD students. The group places a strong emphasis on research excellence and quality of its research publications. The institute has strong ties with the local industry and manages a portfolio of half a dozen research projects in cooperation with industry partners.

The successful candidate will conduct research in the field of data-driven software engineering decision support, within a team that brings together researchers specialized in software analytics, software evolution, software quality assurance, agile development methods, data mining and natural language processing. The research fellow will be expected to contribute to ongoing research projects which aim at exploiting advanced data science methods in one or more of the following application domains:

  • open innovation,
  • energy-efficient software development,
  • software testing.

The research to be conducted is interdisciplinary. In particular, we will be closely collaborating with the natural-language processing group to leverage their expertise on analyzing unstructured data.

Requirements
Candidates must have a PhD in Computer Science or a related discipline. Expertise in at least one of the following topics is essential: software testing, static code analysis, software evolution/maintenance, machine learning. Experience in developing research prototypes and working in collaborative research projects is desirable. The position is not term-limited. Funding is already secured for the first two years of the appointment. The continuation of the position after the first two years will depend on further funding. Remuneration will be up to 2400 euros/month. Estonia applies a flat income tax of 20% on salaries and provides public health insurance for employees.

The expected start date is 1 September 2018, but a later start date can be negotiated.

The deadline for applications is 4 June 2018. The application procedure is outlined in the official advertisement at the University's website.

Postdoctoral research positions in cybersecurity, natural language processing, and experimental social psychology at SUNY Albany

  • Employer: University at Albany, Research Foundation of the State University of New York, ILS Institute
  • Title: Postdoctoral researcher
  • Speciality: Cybersecurity, natural language processing, machine learning, experimental design
  • Location: Albany, New York, USA
  • Deadline: July 31, 2018
  • Date posted: May 18, 2018
  • Contact: Tomek Strzalkowski (tomek {at} albany.edu)

Postdoctoral positions

  • The Personalized AutoNomous Agents Countering Social Engineering Attacks (PANACEA) Project. The PANACEA Project is a joint effort of communication and computer science faculty at the University at Albany, SUNY, as well as researchers at other institutions. The project aims to design, develop, and evaluate an automated system that will protect online users against current and future forms of social engineering attacks. The system will serve as an intermediary between attackers (human, automated, hybrid, coordinated) and the potential victims they target by addressing and eliminating human vulnerabilities in current cyber defense capabilities. The objectives of the project include detection and classification of social engineering attacks as well as active defenses, including engaging and identifying of the attackers.
  • The Computational Ethnography from Metaphors and Polarized Language (COMETH) Project. The COMETH project is a joint effort of computer science and psychology faculty at the University at Albany. The project aims to develop and validate novel computational methodology for automatically acquiring cultural models that represent the worldviews of communities and subcultures operating within the larger society. These models will be obtained using advanced natural language processing and machine learning techniques on data from online media outlets produced by different communities. The objectives of this research include (a) capturing prevalent community attitudes (sentiment and beliefs) toward key concepts such as government, rights, economic inequality, etc.; (b) showing how these attitudes evolve over time, including in response to external influences (e.g., national or international events); and (c) explaining how this system of attitudes acts like an interpretive and defensive tool by allowing the community to reject or distort incoming information.

Requirements for the PANACEA position
For the PANACEA project, we seek a postdoctoral researcher to join our interdisciplinary team. The candidate must have a Ph.D. in Computer Science from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. This position starts September 1, 2018.

  • The candidates are expected to have the following skills: in-depth knowledge of current issues and methods in cybersecurity, natural language processing, socio-behavioral computing, human-computer dialogue, statistical methods of data analysis, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with methods of conversational analysis is a plus.

Requirements for the COMETH positions
For the COMETH project, we seek two postdoctoral researchers: one in computer science and one in psychology. The candidates must have a Ph.D. in Computer Science or Psychology from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. These positions start December 1, 2018.

  • The computer science candidates are expected to have the following skills: in-depth knowledge of current issues and methods in natural language processing, data science, domain modeling, socio-behavioral computing, statistical methods, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with sentiment analysis and metaphor extraction is a plus.
  • The psychology candidates are expected to have following skills: substantial experience with experimental design and advanced statistical methods in experimental social psychology, and knowledge of political psychology. Experience with open science and pre-registration of research protocols will be beneficial.

Overall Requirements

  • For all postdoctoral researchers: duties include advanced research and development under the direction of the project faculty, report preparation and coordination of work of graduate student assistants. Ability to execute substantial tasks within large projects in timely fashion is essential. Candidates must also address in their applications, their ability to work with a culturally diverse population.

The postdoctoral researcher appointment review will begin immediately and will close once filled. The successful candidates will be located in the Institute for Informatics, Logics, and Security Studies at the University at Albany, SUNY. The appointment is for 40 hours a week, initially for 12 to 18 months, and potentially extendible for up to 48 months, depending on the project. Expected start dates are September 1, 2018 and December 1, 2018, pending funding approval from the Federal Government sponsor. The salary is commensurate with experience.

How to Apply

Interested individuals should direct inquiries and submit a cover letter, resume, and three letters of reference to: Prof. Tomek Strzalkowski, Director ILS Institute, University at Albany, tomek {at} albany.edu

Two PhD positions in deep learning for natural language understanding and summarisation at Idiap, Switzerland

  • Employer: Idiap Research Institute, Natural Language Understanding group
  • Title: Two PhD positions
  • Speciality: Natural Language Understanding, Summarisation, Machine Learning
  • Location: Martigny, Switzerland
  • Deadline: May 31, 2018
  • Date posted: April 30, 2018
  • Contact: James Henderson (james.henderson@idiap.ch)

Two PhD positions

The Idiap Research Institute seeks qualified candidates for two PhD student position in the field of natural language understanding, developing deep learning methods for textual entailment and opinion summarisation.

The research will be conducted in the framework of the Swiss NSF funded project Learning Representations of Abstraction for Opinion Summarisation. One of the successful candidates will investigate modelling abstraction relationships between texts (textual entailment), and the other will investigate summarising large collections of opinions (opinion summarisation). Opinion summarisation must abstract away from the details of individual opinions to find consensus statements which are entailed by a significant proportion of opinions.

This project will model these natural language understanding tasks through fundamental advances in representation learning and deep learning architectures. The work will start from Dr. Henderson's work on modelling abstraction in deep learning architectures, where learned vectors represent entailment rather than the usual similarity. Successes in the unsupervised learning of word vectors for entailment will be extended to deep learning architectures for the compositional semantics of texts. Methods for finding the intersection of information in vectors will be extended to clustering texts by their shared content and generating abstract summaries.

The ideal PhD candidate should hold a Master degree in computer science, computational linguistics or related fields. She or he should have a background in machine learning, optimisation, or natural language processing. The applicant should also have strong programming skills.

The successful PhD candidates will join the Natural Language Understanding group at Idiap, under the supervision of Dr. James Henderson. They will also become doctoral students at EPFL conditional on parallel application to, and acceptance by, the EPFL Doctoral School. Appointment for the PhD position is for a maximum of 4 years, provided successful progress, and should lead to a dissertation. Annual gross salary ranges from 47,000 Swiss Francs (first year) to 50,000 Swiss Francs (last year). Starting date is to be negotiated, within 2018. All queries related to the advertised position can be sent to Dr. James Henderson (james.henderson@idiap.ch).

Please apply online here: http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D

Idiap

Idiap is an independent, not-for-profit, research institute funded by the Swiss Federal Government, the State of Valais, and the City of Martigny. It is located in a scenic region in the south of Switzerland, surrounded by the highest mountains of Europe, and offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Idiap is an equal opportunity employer and is actively involved in the "Advancement of Women in Science" European initiative.


2 postdoctoral research positions in text mining and natural language understanding at KU Leuven, Belgium

  • Employer: KU Leuven, Department of Computer Science, Language Intelligence and Information Retrieval lab
  • Title: Postdoctoral researcher
  • Speciality: Text mining, natural language understanding, machine learning
  • Location: Leuven, Belgium
  • Deadline: May 21, 2018
  • Date posted: April 23, 2018
  • Contact: Sien Moens (sien.moens {at} cs.kuleuven.be)

Postdoctoral positions

  • Postdoctoral position on the topic of multilingual text mining. The goal is to build interlingual representations that allow multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. This postdoctoral position will be funded by the EU ITEA3 grant PAPUD and offers a contract for two years. The position will start as soon as possible.
  • Postdoctoral position on the topic of multimodal representation learning. The goal is to learn continuous representations that represent language grounded in visual perception (static images and video), assist in the design of novel machine learning architectures, and investigate suitable data structures for real-time search of the representations. This postdoctoral position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS and offers a contract for two years (with the possibility of renewal for another two years). The position will start September 1, 2018.

Requirements

  • PhD in computer science or equivalent.
  • Motivated interest in and preferably knowledge of (as demonstrated by publications in highly recognized venues such as ACL, EMNLP, ICML, NIPS, etc.) of natural language processing and machine learning, including deep learning and learning of latent variable models. For the second postdoctoral position, interest or experience in semantic hashing is a plus.

The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!

2 PhD positions in natural language understanding at KU Leuven, Belgium

  • Employer: KU Leuven, Department of Computer Science, Language Intelligence and Information Retrieval lab
  • Title: PhD researcher
  • Speciality: Natural language understanding, machine learning
  • Location: Leuven, Belgium
  • Deadline: May 21, 2018
  • Date posted: April 23, 2018
  • Contact: Sien Moens (sien.moens {at} cs.kuleuven.be)

PhD positions

  • PhD position on the topic of multimodal representation learning trained on language and visual data. The goal is to learn continuous representations of language grounded in visual data (static images and video) including the design, implementation and evaluation of novel machine learning architectures that capture textual as well as visual grammars. The learned representations will serve as commonsense knowledge in language understanding tasks. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.
  • PhD position on the topic of semantic parsing of natural language sentences and discourse. The goal is to learn compositional models that take into account continuous representations of objects, their attributes and likely relationships. An additional focus is on using the compositional models to efficiently parse language in real-time. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.

Requirements

  • Master degree in computer science or equivalent.
  • Motivated interest in and preferably knowledge of (as demonstrated in master thesis or master course work) of natural language processing, machine learning, including deep learning and learning of latent variable models, semi-supervised machine learning, and constrained optimization.

The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!

Associate Research Scientist (NLP, machine learning and text mining), TU Darmstadt

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

Associate Research Scientist (PostDoc- or PhD-level; for a term of three years with an extension option)

This position is intended to strengthen the profile of the lab in a research area within natural language processing (NLP), machine learning and text mining, such as word-/sentence-/discourse-level semantics, robust textual inference, and the applications of the above in higher-level NLP, such as QA, text summarization, argument mining, etc. The lab closely cooperates with the groups in machine learning, computer vision, and interactive data analytics of the Computer Science department and many other research labs and companies. Besides, the lab conducts research projects in close cooperation with the users in the humanities and social sciences.

We ask for applications from highly qualified candidates with a specialization/PhD in NLP/Text Mining, preferably with relevant research and teaching experience and strong communication skills in English and German (optional). Individual career development plans can be worked out. E.g. the successful candidate will contribute to research activities described above and – based on the previous experience and qualifications – will be given an opportunity to grow, i.e. to teach courses, co-supervise PhD students, and manage research projects. Outstanding candidates (at M.Sc.-level, without a PhD) are invited to apply and can be considered for a PhD-level position with an adjusted scope of responsibilities. The position being filled is based on the university funds.

The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG and the BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members.

Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the application form by March 28, 2018. The position is open until filled.

PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Natural Language Processing and Machine Learning

The Research Training Group "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES), which has been established in 2015 at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling two positions for three years, starting as soon as possible, located in Darmstadt and associated with UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.

The positions provide the opportunity to obtain a doctoral degree with an emphasis in natural language processing tasks such as structured summaries of complex contents, in content selection and classification enhanced by reasoning, or a related area.

The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, computer vision, and automated quality assessment will be developed. AIPHES will investigate a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.

AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS). AIPHES strives to publish its results at leading scientific conferences and is actively supporting its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.

Prerequisites

We are looking for exceptionally qualified candidates with a degree in Computer Science, Machine Learning, NLP, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Prior experience in scientific work is a plus. Applicants should be willing to work on lesser-resources languages, e.g. German, and, if necessary, to acquire basic German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.

The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. UKP Lab is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members. Its BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, machine learning and text mining. The large-scale argument mining project allows searching large document collections in response to a user-defined topic: neural networks determine relevant pro and con arguments in real-time, and represent them in a concise summary.

Applications should include a motivational letter that refers to one of the planned research areas of AIPHES, a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by April 3rd, 2018: https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/

In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.

Tenure track at IDSIA (Switzerland) in Natural Language Understanding and Text Mining

  • Employer: IDSIA (www.idsia.ch)
  • Title: Tenure track
  • Specialty: Natural Language Understanding and Text Mining
  • Location: Lugano, Switzerland
  • Deadline: March 31th, 2018 (start date flexible)
  • Date posted: March 16, 2018
  • Contact email: Giorgio Corani (giorgio.corani@supsi.ch)

Project Description
The person hired on this position will evenly share her/his working time on two main activities:

  • Basic research, aiming at publications in highly rated journals and international conferences;
  • Applied research, collaborating with industrial partners in cutting-edge projects.

A further cross-activity will be contributing to search for funding opportunities of both basic and applied research.

The involved research area regards natural language understanding (probabilistic language modeling, keyword extraction, text summarization), text mining (text classification, word embedding, topic models) and semantic analysis of the text.

Requirements

  • The position is for a young researcher who has already obtained a PhD on a topic relevant to Natural Language Processing and/or Text Mining;
  • Master in informatics or other areas with strong emphasis on computation;
  • Excellent programming skills and deep knowledge of libraries for natural language processing;
  • Communication and collaboration skills.
  • Proficiency in written and spoken in English.


Optional but preferential

  • Strong publications record;
  • Capability of leading projects carried out with industrial partners on automatic analysis of documents;
  • Good knowledge of machine learning algorithms and tools;
  • Good knowledge of written and spoken Italian, or willingness to learn it in short times.

We offer

  • A tenure track position (degree of occupancy 100%)
  • International working environment;
  • Collaboration with a strong team of researchers in Machine Learning and Statistics (our publication record is available at: [8]);
  • Salary starting from 80,000 CHF / year (about 84,000 $/year)

Application
Applicants should submit the following documents, written in English:

  • curriculum vitae
  • list of exams and grades obtained during the Bachelor and the Master of Science;
  • list of three references (with e-mail addresses);
  • brief statement on how their research interests fit the topics above (1-2 pages);
  • publications list and possibly link to the thesis.

Applications should be submitted through the Application website

Postdoctoral position in Psychology at University of Pennsylvania

  • Employer: University of Pennsylvania
  • Title: Postdoctoral Researcher
  • Specialty: Computational Linguistics
  • Location: Philadelphia, Pennsylvania
  • Deadline: March 20th, 2018 (start date flexible)
  • Date posted: February 27, 2018
  • Contact email: Sudeep Bhatia (bhatiasu@sas.upenn.edu)

Project Description
The researcher will study how word embeddings and related techniques can be used to model how people represent objects and events, and, in turn, predict human probability judgment, event forecasting, social judgment, risk perception, and consumer behavior.

Requirements
Candidates should have completed (or should be about to complete) a PhD in Computer Science, Psychology , Cognitive Science, or related fields, and should be interested in applying natural language processing to address questions in Psychology, Policy, Economics, and Marketing. Applicants should have graduate-level expertise in natural language processing and machine learning.

Additional Details
The position will be based in the Psychology department at the University of Pennsylvania, and will be supervised by Sudeep Bhatia. Lyle Ungar will serve as a second advisor. The postdoctoral researcher will also be encouraged to interact with the broader intellectual community at Penn. The appointment is expected to begin Sept 1, 2018 (start date is flexible). The term of hiring is one year, renewable for up to one additional year. The position is full time and there are no teaching or administrative responsibilities.

How to Apply
Applications for the positions must be submitted by March 20th, 2018, to ensure full consideration. However, review of applications will continue until the position is filled. Applicants should email a curriculum vitae and contact information for two references to Sudeep Bhatia at bhatiasu@sas.upenn.edu.

Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology

  • Employer: Rochester Institute of Technology
  • Title: Postdoctoral Research Scientist
  • Specialty: Postdoctoral Research Scientist: Computational Linguistics
  • Location: Rochester, New York, United States
  • Deadline: Open until filled
  • Date posted: February 17, 2018
  • Contact: Cecilia O. Alm (coagla@rit.edu)
  • Job listing

We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.

Required Minimum Qualifications:

  • PhD., with training in Computational Linguistics, Linguistics, or an allied field
  • Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly
  • Publication record and plan for research and grant seeking activities
  • Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences

Required Application Documents:
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement

How To Apply:
Please apply at: http://careers.rit.edu/staff. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.

Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan

  • Employer: University of Michigan
  • Title: Research Fellow
  • Specialty: Postdoctoral Research Fellow: Automated Text Analysis
  • Location: Ann Arbor, Michigan, United States
  • Deadline: March 12, 2018, desired start June 2018
  • Date posted: February 12, 2018
  • Official Job Listing - Application Page

How to Apply
A cover letter is required for consideration for this position and should be included as the first page of your CV. The cover letter should outline your specific interest in the position and outline skills and experience that directly relates to this position.

Job Summary
A generously funded project (2016-2021) welcomes applicants with interest in and expertise in automated text analysis. The project, M-Write, brings together researchers from writing studies, the natural sciences, and computer programming to investigate how Writing-to-Learn pedagogies promote conceptual learning by students in large-enrollment gateway courses. Students write in response to carefully crafted assignments, participate in automated peer review, and then revise their drafts. Approximately 10,000 students have already participated in M-Write courses, which means that there is already a large corpus of student writing and peer review responses, with more being added each semester. We seek a specialist in automated text analysis to join the research team. Goals include principled corpus compilation, analysis, and development of corpus-driven algorithms to support student learning of key concepts highlighted in assignments.

This position will be a 12-month Post-Doctoral Fellowship beginning in June 2018 with possibility of renewal. The salary is negotiable.

Responsibilities

  • Retrieve and create corpora for NLP and associated linguistic analysis
  • Develop and test systems for identifying students who appear to lack key concepts as defined by lexical and grammatical structures, discourse analysis, and possible sentiment analysis
  • Design a data warehouse that will facilitate the ability to collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research leading to peer-reviewed publications, and future external funding
  • In collaboration with other project staff collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research that could lead to peer-reviewed publications
  • Organize, synthesize, and analyze project data, and write co-authored papers with project PIs for peer-reviewed articles

Required Qualifications
Ph.D. in computational linguistics, natural language processing, machine learning, cognitive linguistics, sentiment analysis or related area. Previous research experience in textual analysis in terms of syntax (e.g. parts of speech tagging), semantics (e.g. topic segmentation) and discourse analysis is essential. Research in statistical modeling is also required. Strong computer science skills are essential, and data warehouse design skills are highly desired. Background in the theory and research of writing-to-learn pedagogies and experience with educational technology in natural language processing are desired but not required.

Background Screening
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.

U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.


CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing

  • Employer: University of Colorado Boulder
  • Title: Postdoctoral Associate
  • Specialty: Machine Learning, Speech and Language Processing
  • Location: Boulder, Colorado, United States
  • Deadline: Ongoing, desired start August 2018
  • Date posted: February 9, 2018
  • Contact: Dr. Sidney D’Mello

Postdoc in Machine Learning with an Emphasis on Speech and Language Processing
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)

The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting August 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.

The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving).

The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science.

The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.

Required

  • Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire
  • Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)
  • Evidence of a strong publication record in the aforementioned areas

Desired

  • Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling

Job Details

  • One year initial position with possible extension to a second and third year based on performance and availability of funds
  • Desired start date is August 2018. However, start date is negotiable
  • Competitive salary with benefits commensurate with qualifications

How to Apply
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications as a single PDF document named FirstNameLastName.pdf.

Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references

About the University of Colorado and the City of Boulder
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.

The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.

Special Instructions to Applicants
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.

The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at adacoordinator@colorado.edu.


Full-time Researchers, IBM Research - Almaden

  • Employer: IBM Research - Almaden
  • Title: Research Staff Member
  • Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas
  • Location: San Jose, California, USA
  • Deadline: June 1, 2018
  • Date posted: January 31, 2018
  • Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)


IBM Research - Almaden is looking for talented researchers with background in Natural Language Processing and Machine Learning to join the Natural Language Processing, Entity Resolution and Discovery Department. We are actively building the next-generation knowledge engineering platform for the creation, maintenance and consumption of "industry-specific" knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such industry-specific knowledge bases are the foundation of many emerging AI services and applications.

Such a platform needs to support the entire life cycle for knowledge engineering including:

  • Creation, maintenance and evolution of domain schema to capture domain concepts of interest
  • Scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources, including text analytics, entity resolution and integration, cleansing, data transformations and machine learning
  • Domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages
  • Scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process
  • Techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries
  • Easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces
  • Incorporating crowd sourcing and continuous evolution of the system through learning from user interactions

The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact.

The research is being conducted in close collaboration with the IBM Watson division and multiple global IBM Research labs (Australia, India, and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains).

We are currently looking for talented researchers with interest in system design and implementation as well as experience in one or more areas relevant to the knowledge engineering life cycle as described above, particularly those with background in Natural Language Processing and Machine Learning. You will participate in cutting edge research, build at industrial scale, and keep connected to the larger research community by regularly publishing papers and partnering with universities.

Required

  • Bachelor's degree or equivalent in Computer Science, related technical field or equivalent practical experience.
  • Programming experience in one or more of the following: Java, C, C++ and/or Python.
  • Experience in Natural Language Processing, Computational Linguistics, Machine Learning, Large-Scale Data Management, Data Mining or Artificial Intelligence
  • Contribution to research communities and/or efforts, including publishing papers at conferences such as ACL, EMNLP, NIPS, AAAI, ICML, SIGMOD, VLDB, and KDD.

Preferred

  • PhD in Computer Science, related technical field or equivalent practical experience.
  • Relevant work experience, including experience working within the industry or as a researcher in a lab.
  • Ability to design and execute on research agenda.
  • Strong publication record.


PhD-level Researchers, AIPHES, Darmstadt/Heidelberg

PhD positions in DFG Graduate School AIPHES: Natural Language Processing and Computational Linguistics

The Research Training Group “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES), which has been established in 2015 at Technische Universität Darmstadt and at Ruprecht Karls University Heidelberg is filling several positions for three years, starting as soon as possible. Positions remain open until filled.

The positions provide the opportunity to obtain a doctoral degree in the research area of the training group with an emphasis, e.g., in opinion and sentiment - extrapropositional aspects of discourse, in natural language processing tasks such as structured summaries of complex contents, in content selection and classification enhanced by reasoning, or a related area. The group will be located in Darmstadt and Heidelberg. The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale.

The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, computer vision, and automated quality assessment will be developed. AIPHES will investigate a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.

Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS).

AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and will actively support its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.


Prerequisites

We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be willing to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.

The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. The Institute for Computational Linguistics (ICL) of the Ruprecht Karls University Heidelberg is one of the largest centers for computational linguistics both in Germany and internationally. The ICL and the NLP department of the HITS jointly run the graduate program “Semantic Processing” with an integrated research training group “Coherence in language processing: Semantics beyond the sentence”, which has a close connection to the topics in computational linguistics of AIPHES.

Applications should include a motivational letter that refers to one or two of the planned research areas of AIPHES, a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by February 11th, 2018:

https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/

In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.


Associate Research Scientist, UKP Lab, TU Darmstadt

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

Associate Research Scientist (PostDoc- or PhD-level; for an initial term of two years)

in the areas of Interactive Text Analysis, the UKP Lab is looking for a researcher with a background in Natural Language Processing and Software Development to work on the project INCEpTION funded by the German Research Foundation (DFG). The project is developing a comprehensive interactive text analysis platform to improve efficiency and to enable new ways of exploring, annotating and analyzing large-scale text corpora through the use of assistive features based on machine-learning.

We ask for applications from candidates from Computer Science with a specialization in Natural Language Processing, Text Mining, or Machine Learning, preferably with expertise in research and development projects, and strong communication skills. The successful applicant will work on research and development activities regarding text annotation by end-users (researchers, analysts, etc.), information recommendation, and create the corresponding text analysis platform. Ideally, the candidates should have demonstrable experience in designing complex (NLP and/or ML) systems (frontend and backend), in applying NLP-related Machine Learning-based methods, and strong programming skills especially in Java. Experience with neural network architectures and demonstrable engagement in open source projects are strong pluses.

The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), with a rapidly developing focus on Interactive Machine Learning and who provide a range of high-quality open source software packages for interactive and automatic text analysis to research and industry communities.

UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent work environment. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest standards, cooperative work style and close interaction of team members.

Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).

Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the applications to: jobs@ukp.informatik.tu-darmstadt.de by 16.2.2018. The positions are open until filled. Later applications may be considered if the position is still open.

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