Difference between revisions of "Employment opportunities posted 2019"

From ACL Wiki
Jump to navigation Jump to search
 
(No difference)

Latest revision as of 06:03, 2 June 2020

  • This is an archive of employment opportunities that were posted in 2019.

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"

Retrieved from "https://aclweb.org/aclwiki/index.php?title=Employment_opportunities_posted_2019&oldid=12887"