Employment opportunities, postdoctoral positions, summer jobs

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Internship positions available in Natural Language Processing at Adobe Research

  • Employer: Adobe Systems Incorporated
  • Title: NLP Scientist Intern
  • Natural Language Processing, Machine Learning, Question Answering and Dialog Systems.
  • Location: San Jose, CA
  • Deadline: open until all the positions are filled
  • Date Posted: December 23, 2015
  • Trung Bui: bui@adobe.com

Description: We are looking for several NLP scientist interns who will work on semantic understanding, question answering and dialog systems to improve Adobe digital media and digital marketing products. The internship will be at the Medial Intelligence Lab under the Imagination Lab at Adobe Research (http://www.adobe.com/technology.html) located in San Jose, California. It is 13 weeks long and can start any time from March 1, 2016.

Key Qualifications

  • Experience with semantic parsing, question answering and dialog systems.
  • Experience with machine learning, deep learning.
  • Good programming skills in Java/C++ and/or Python

Education M.S. or PhD student in Computer Science or related field

Additional Requirements No.

Associate Research Scientist at UKP Lab, TU Darmstadt

  • Employer: UKP Lab, Department of Computer Science, Technische Universität Darmstadt
  • Title: Associate Research Scientist
  • Speciality: Natural Language Processing
  • Location: Darmstadt, Germany
  • Deadline: January 15, 2016
  • Date posted: December 23, 2015
  • Contact: jobs@ukp.informatik.tu-darmstadt.de

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) to strengthen the group's profile in the area of Computational Argumentation. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Computational Argumentation is one of the rapidly developing focus areas in collaboration with industrial partners.

We ask for applications from candidates in Computer Science, Information Systems, Business Information Technology, or Computational Linguistics, preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of computational argumentation (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and experience in information retrieval, large-scale data processing and machine learning. In particular, experience with deep-learning is a strong plus. Combining fundamental NLP research on Computational Argumentation with industrial applications from different application domains will be highly encouraged.

UKP's wide cooperation network both within its own research community and with partners from 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 initiative "Knowledge Discovery in the Web" and the recently established Research Training Group "Adaptive Information Processing of Heterogeneous Content" (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, 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.

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 application to: jobs@ukp.informatik.tu-darmstadt.de by 15 January 2016. The position is open until filled. Later applications may be considered if the position is still open.

Postdoctoral Researcher position in NLP/Computational Social Science at UPenn

  • Employer: Computer & Information Science, University of Pennsylvania, USA
  • Title: Postdoctoral Researcher
  • Speciality: Natural Language Processing, Computational Social Science
  • Location: Philadelphia, USA
  • Deadline: January 15, 2016
  • Date posted: December 21, 2015
  • Contact: applications@wwbp.org

We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression.

The ideal candidate will have research experience in computational linguistics and applied machine learning. She or he will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwbp.org for example publications.

  • Application Deadline: January 15, 2015
  • Approximate Start Date: March 1, 2016 (but flexible)

How to Apply: Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line.

The University of Pennsylvania is an EOE/Affirmative Action Employer. Position contingent on funding.

Primary Contact: Professor Lyle Ungar, ungar@cis.upenn.edu


Multiple positions as Full-time researcher, Post-doc researcher, Software Engineer and Summer Intern in IBM Research - Almaden, San Jose

  • Employer: IBM Research - Almaden
  • Title: Researcher, Software Engineer, Post-doc, Summer Intern
  • Speciality: natural language processing, information integration, entity resolution, machine learning, ontologies, and large-scale data management
  • Location: San Jose, CA
  • Deadline: (until filled)
  • Date posted: December 18, 2015
  • Contact: Laura Chiticariu (chiti {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)


IBM Research - Almaden is looking for researchers to join the Natural Language Processing, Entity Resolution and Discovery Department. Our research focuses around creating a 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 a platform needs to support the entire lifecycle for knowledge engineering including:

  • creation, maintenance and evolution of ontologies 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 such as text analytics, entity resolution and integration, cleansing, data transformations and machine learning; supporting 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 academic, industrial and open source impact:


The research is being conducted in close collaboration with the IBM Watson Solutions division and multiple global IBM Research labs (India, Haifa 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 researchers (Research Staff Members, software engineers, post-doc researchers and summer interns) with interest & experience in one or more areas relevant to the knowledge engineering life cycle such as natural language processing, information integration, entity resolution, machine learning, ontologies, and large-scale data management, as described above.


Please send your resumes to: Laura Chiticariu (chiti {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)

Two Postdoc Opportunities at the US Army Research Lab in the Washington, DC Metro Area

  • Employer: US Army Research Laboratory
  • Title: Postdoctoral Fellow
  • Speciality: Knowledge Representation, Knowledge Bases, Common-Sense Reasoning, Planning
  • Location: Adelphi, MD
  • Deadline: (until filled)
  • Date posted: November 30, 2015
  • Contact: douglas.a.summers-stay.civ@mail.mil and/or ethan.a.stump2.civ@mail.mil

The US Army Research Laboratory currently has two postdoc opportunities:


Position #1

The US Army Research Laboratory (ARL) is researching common-sense reasoning and natural language understanding for the purpose of creating a communication dialogue to promote increased intent understanding within Human-Robot teams. In support of this effort, ARL is looking for an individual with a PhD or equivalent, with interest and a background in knowledge representation, knowledge bases, knowledge graphs, common-sense reasoning, or spatial reasoning. We plan to make use of semantic vector spaces to enhance the capabilities of the reasoning system, so some familiarity with knowledge graph embedding, distributional semantic vector spaces (such as GloVe or word2vec), or learning from massive text corpora would also be beneficial.

The position is available immediately with a duty location at the Adelphi Laboratory Center (ALC), Adelphi, MD.

To learn more about the position, or to apply, please send questions or a CV to Dr. Douglas Summers-Stay via email at douglas.a.summers-stay.civ@mail.mil.


Position #2

The US Army Research Laboratory (ARL) is seeking a Postdoctoral Researcher to bridge the gap between humans and autonomous systems by developing a controlled language to reason and communicate about human intent as it applies to commands a robot receives. In robotics, practitioners often program autonomous systems by developing monolithic behaviors that, when correctly parameterized, will cause the system to act as desired. However, setting these parameters is often more art than science, and we cannot expect an average user to effectively task the system unless they have only the simplest tasks in mind. ARL desires a controlled language that both concisely describes the capabilities of autonomous systems, as well as enables common-sense reasoning and representation of implicit goals that will let the system fill instructional gaps from novice users.

In this position, the Researcher will work on a cross-disciplinary team comprised of researchers in computational linguistics, computer vision, machine learning, and experimental robotics to develop a system for interacting with humans—the goal being to develop and evolve complex plans carried out by autonomous systems. The primary responsibilities of the Researcher will be learning how we can use language to link the domains of intent reasoning and action, and developing such a language to enable experiments with humans and robot teams operating in dynamic environments.

The candidate must have a PhD or equivalent degree, and should have an interest and background in formal methods, knowledge representation and reasoning, computational linguistics, control policies, or AI planning.

The position is available immediately with a duty location at the Adelphi Laboratory Center (ALC), Adelphi, MD.

To learn more about the position, or to apply, please send questions or a CV to Dr. Ethan Stump via email at ethan.a.stump2.civ@mail.mil.


Open PhD position on Textual Knowledge Resources (NLP / IR / ML) at Data and Web Science Group in Mannheim, Germany

  • Employer: The Data and Web Science Research Group, University of Mannheim, Germany
  • Title: PhD Candidate (post-Masters)
  • Speciality: Natural Language Processing, Information Retrieval, Knowledge Bases
  • Location: Mannheim, Germany
  • Deadline: January 6, 2016
  • Date posted: November 20, 2015
  • Contact: queripidia-jobs(At)uni-mannheim(DoT)de

The Information Retrieval and Natural Language Processing Group at the University of Mannheim invite applications for

ONE PHD STUDENT IN STATISTICAL NLP / IR / MACHINE LEARNING

The student is expected to contribute to a project on Knowledge Consolidation and Organization for Query-specific Wikipedia Construction under the principal investigator Laura Dietz. The goal of the research project is to make information on the Web accessible in a Wikipedia-like form through a query-driven interaction paradigm. This research requires a combination of methods from information retrieval and automatic text understanding to provide the user with a synthesis of the information through summarization, sub-topic identification, and article organization.

We are particularly interested in candidates with a background in one or several of the following areas:

  • statistical text processing (e.g., automatic summarization, event extraction and ordering)
  • machine learning
  • knowledge base construction
  • information retrieval
  • distributed large-scale processing

Applicants must have a Masters degree (or obtain it in the near future) in Computer Science, Natural Language Processing or Machine Learning with previous research experience in information retrieval and human language technologies is a plus. The successful candidate is expected work under limited supervision, and publish papers at top level conferences and journals and collaborate with other members of the research group.

Duration: initially one year (starting in Spring 2016) with possible extension of three years.

Salary range: according to German public scale TV-L 13 100% (full time, commensurate with experience and qualifications, ranging between 3200 and 4.600 Euro before taxes).

Please submit your application per e-mail (queripidia-jobs(At)uni-mannheim(DoT)de) as a single PDF. This PDF should include a short research statement, CV, copy of university degrees, a list of publications and published software and contact details of three references. All applications sent before January 6, 2016 will receive full consideration. The position remains open until filled.

The Data and Web Science Group is a joint lab of several professors covering diverse topics on managing, integrating and mining large-amounts of heterogeneous information within enterprise and open Web contexts. Further information about the group can be found at http://dws.informatik.uni-mannheim.de/ .

The University of Mannheim is committed to increase the percentage of female scientists and encourages female applicants to apply. Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.

Please contact Laura Dietz (queripidia-jobs(At)uni-mannheim(DoT)de) for informal enquiries.

Job posting at: http://bit.ly/1MWXjo1


Research position in Natural Language Processing/Text Mining, University of Manchester

  • Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
  • Title: Postdoctoral Research Fellow
  • Speciality: Natural Language Processing, Text Mining
  • Location: Manchester, UK
  • Deadline: October 19, 2015
  • Date posted: November 15, 2015
  • Contact: sophia.ananiadou@manchester.ac.uk

Applications are invited for a senior research fellow in Clinical Text Mining at the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk) , School of Computer Science, University of Manchester.

Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing/Text Mining; working experience in information extraction at large scale; excellent knowledge in developing and adapting algorithms for text mining systems; machine learning; experience in biomedical/clinical Natural Language Processing/Text Mining; strong track record of high-quality papers in conferences such as ACL, EMNLP, Coling, etc., and in high quality journals; excellent Java skills; proven ability to develop research proposals independently.

The objectives of this post are to conduct research into extracting complex information from the scientific literature and clinical case reports to facilitate the discovery of biomarkers using adaptive natural language processing and text mining methods.

  • Duration of post: 1st November 2015 for 48 months
  • Salary: £38,511 to £42,067 per annum

Research Environment

The National Centre for Text Mining has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology management, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.manchester.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research".

The project involves collaboration with a large team working in a newly created interdisciplinary research centre (Manchester Molecular Pathology Innovation Centre, MMPathIC) funded by MRC/EPSRC, focusing on personalised medicine, improving diagnosis and treatment of inflammatory diseases, validating and evaluating biomarkers for improving patient outcomes.

Informal enquiries can be made to Prof. Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk)

Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=10521

PhD Position: Deep Learning and Random Forest for Argumentation Mining

  • Employer:University of Liège, Liège, Belgium
  • Title: PhD Candidate
  • Speciality: Natural Language Processing, Text Mining
  • Location: Liège, Belgium
  • Deadline: November 23, 2015
  • Date posted: October 8, 2015
  • Contact: ashwin.ittoo@ulg.ac.be

The overall goal of this PhD project is to contribute to and advance the nascent field of AM. The selected candidate will have the opportunity to develop novel AM algorithms, which will then be applied to online reviews to evaluate their performance and to determine whether the presence of argumentative patterns are predictive of the helpfulness of online reviews.

The candidate will investigate the performance of two recent machine learning paradigms, Deep Learning and Random Forests. The candidate will develop a sound understanding of these paradigms and propose novel Deep Learning and Radom Forest algorithms for AM. Other recent machine learning paradigms, in particular, minimally-supervised learning and distant supervision, will also be investigated. The proposed algorithms will be applied to online reviews in order to automatically detect argumentative patterns from the textual contents and determine whether the presence of these patterns influence the reviews’ helpfulness scores of

Several corpora are already available for evaluation: product and service reviews from Amazon (books, movies), YELP and TripAdvisor. In addition, access to the Penn Discourse TreeBank (PDTB) is also available.

The selected candidate will be based at the HEC Management School, the University Liège, within the Operations department. Members of this department are engaged in research and teaching in “quantitative methods” (Operations Research, Machine Learning/Data Mining/Analytics, Enterprise Information Systems, Supply Chains and Logistics). The candidate will also collaborate with other international scholars in Japan, the Netherlands and France.

The PhD project will span over a period of 4 years and the candidate will be hired as a full-time PhD scholar. The gross salary will be around 2150 EUR per month (net: ~ 1800-1990 EUR). Interested candidates are required to send their CV (incl. publications if any) and a letter of motivation via e-mail to Prof. Ashwin Ittoo, ashwin.ittoo@ulg.ac.be by 23rd November 2015. Please clearly indicate ‘PhD application’ in the subject line. Only those candidates deemed most suitable for the research position will be contacted. The starting date is negotiable, but we would prefer candidates who could start soonest.


Research Associate in Natural Language Processing and Machine Learning, National Centre for Text Mining, University of Manchester

  • Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
  • Title: Research Associate
  • Speciality: Natural Language Processing, Text Mining
  • Location: Manchester, UK
  • Deadline: October 3, 2015
  • Date posted: September 25, 2015
  • Contact: sophia.ananiadou@manchester.ac.uk

Applications are invited for a researcher in NLP and machine learning at the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk), School of Computer Science, University of Manchester.

The candidate will be joining a strong team with 10+ staff at NaCTeM carrying out cutting edge research in NLP, biomedical text mining and machine learning. The post is funded by the Medical Research Council and focuses on developing new algorithms for unsupervised and semi-supervised methods in information extraction, topic analysis, active learning, text classification using deep learning/neural networks to support the development of systematic reviews at the National Institute for Health and Care Excellence.

Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing and Machine Learning; excellent knowledge in unsupervised NLP methods, deep learning, neural networks; excellent knowledge in topic analysis, clustering and classification; track record of high-quality papers in conferences such as ACL, EMNLP, etc., and excellent programming skills.

  • Duration of post: 1st November 2015 for 24 months
  • Salary: £30,434 to £37,394 per annum

Research Environment

The National Centre for Text Mining has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology management, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.manchester.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research". NaCTeM is collaborating closely with the newly created Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST) in Japan (https://unit.aist.go.jp/airc//index.en.html), which focuses among others on data-knowledge integration, machine learning, natural language processing and text mining. The candidate will benefit from research stays and interactions with the team in Japan.

Informal enquiries can be made to Prof. Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk)

Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=103224.


Research Positions at AIRC (Artificial Intelligence Research Center), Japan

  • Employer: Artificial Intelligence Research Center (AIRC), National Institute for Advanced Industrial Science and Technology (AIST)
  • Title: Post-doctoral research fellows
  • Speciality: Machine Learning, Deep Learning, Neuro-Computing, Natural Language Processing, Text Mining
  • Location: Tokyo, Japan
  • Deadline: October 16, 2015
  • Date posted: September 25, 2015
  • Contact: airc-recruit-ml@aist.go.jp

Applications are invited for several positions in Artificial Intelligence at the Artificial Intelligence Research Center (AIRC) (https://unit.aist.go.jp/airc//index.en.html) under the auspices of the National Institute for Advanced Industrial Science and Technology (AIST) (http://www.aist.go.jp/index_en.html). Successful candidates will join a strong and expanding team of 35+ full-time researchers carrying out cutting edge research in AI.

Research at AIRC includes Machine Learning, Deep Learning, Planning and Search, Text Mining, NLP, Pattern Recognition, Brain Inspired Computation, and infrastructures for AI．With strong research links to industrial partners, there is a particular emphasis on applications of AI technology to real world problems as well as research into theories and fundamental AI technologies. We work in close cooperation with partners in both the private and public sector to cover a broad range of AI applications, including:


  • Artificial Intelligence for Human Life: Health-care, Smart city and Smart home, Innovative Retailing and Tourism, etc.
  • Artificial Intelligence for Manufacturing and Engineering: Intelligent Robots, Intelligent planning and control of manufacturing plants, etc.
  • Artificial Intelligence for Big Sciences: AI applications in Bio-Medical Science and Material Science, Geology, Computational Sociology, etc.


The advertised posts are funded by a project supported by NEDO (http://www.nedo.go.jp/english/index.html), which aims to establish a core research center for AI in Japan. Depending on the expertise and interest of the candidate, s/he will focus either on basic research or application related research of AI to real world problems. AIRC will carry out research in close cooperation with national or international research institutions such as Riken, CMU, Toyota Technology Institute in Chicago, the University of Manchester and DFKI.


Candidates should have a PhD in Computer Science with an emphasis on one of the following areas: Machine Learning, Deep Learning, Neuro-Computing, Planning and Search, Natural Language Processing, Text Mining, and Algorithms and Infrastructures for Big Data Analysis. Excellent programming skills and an excellent track-record of high-quality papers in top-tier conferences and journals would be a definite advantage.


We have three categories of post-doctoral research fellows. The duration of employment for all three categories is initially 24 months, with a possible extension of 36 months or longer, depending on performance. The starting date of employment will be 1st December 2015 at the earliest.

  • Category A: Post-Doctoral Research Fellow - Salary 5,500,000 JPY to 7,000,000 JPY per annum
  • Category B: Senior Post-Doctoral Research Fellow - Salary 7,000,000 JPY to 10,000,000 JPY per annum
  • Category C: Distinguished Research Fellow - Salary 10,000,000 JPY per annum


Research Environment


AIST is one of the largest publicly funded research institutes in Japan and a single research institute under the Ministry of Economy, Trade and Industry (METI). AIRC is the newest research center within AIST, established in May, 2015. As a core research center of AI in Japan, we have been establishing close cooperation with researchers at Japanese and international institutes, which include the University of Tokyo, Tokyo Institute of Technology, Riken, Osaka University, Tohoku University, National Institute of Informatics, Toyota Technology Institute in Chicago, CMU, University of Manchester and DFKI.


AIRC is located in Odaiba, which is in one of the central districts of Tokyo, a bustling international city and the capital of Japan. Tokyo offers both the modern urban lifestyle of Japan as well as a rich Japanese heritage.

Interested candidates are invited to send, via electronic mail, the following items to the Director of Artificial Intelligence Research Center (AIST), Prof. Junichi Tsujii (airc-recruit-ml@aist.go.jp):

  • A cover letter that clearly indicates their main research interests
  • Curriculum Vitae
  • The contact details of 3 referees
  • Copies of maximum of 3 publications that you have (co-)authored, and which are representative of your past research achievements. Each publication should be accompanied by a short summary that highlights its major contributions
  • An agenda of future research goals. This should be no longer than one page, including figures

Informal enquiries can be made to airc-recruit-ml@aist.go.jp


NOTE: Please send your application to airc-recruit-ml@aist.go.jp directly via e-mail, and not by post. It is NOT necessary to follow the specific CV formats specified on the AIRC website.


Open Rank Tenure Line Position in Linguistics at Northwestern University

  • Employer: Northwestern University
  • Title: Tenure-Line Professor (open rank)
  • Speciality: Open area
  • Location: Evanston, IL, USA
  • Deadline: December 1, 2015
  • Date posted: August 31, 2015
  • Contact: matt-goldrick@northwestern.edu

The Department of Linguistics at Northwestern University seeks to fill a tenure-line position (open rank) with a start date of September 1, 2016. We are looking for candidates who pursue an integrated approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The candidate will join a vibrant interdisciplinary language sciences community including researchers from cognitive science, cognitive neuroscience, computer science, philosophy, psychology, and speech science.

We seek exceptional candidates with forward-looking research programs that hold the promise of future external funding. Applicants that wish to be considered for appointment at the rank of Associate Professor or Professor are expected to have a record of excellence in research and teaching, success in obtaining external funding, and to have held both internal and external leadership roles.

To receive fullest consideration, applications should arrive by December 1, 2015. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV (including contact information), statements of research and teaching interests, reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names of three references (with their contact information). Please visit http://www.linguistics.northwestern.edu/ for online application instructions.

E-mail inquiries should be directed to Matt Goldrick, Chair (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.


One PHD / POSTDOC position in Text Analysis at the University of Mannheim

  • Employer: The Data and Web Science Research Group, University of Mannheim, Germany
  • Title: PhD or Postdoctoral Research Fellow
  • Topics: Natural Language Processing
  • Location: Mannheim, Germany
  • Deadline: September 15, 2015
  • Date Posted: August 20, 2015
  • Contact: sfb884@informatik.uni-mannheim.de

The researcher is expected to contribute to the C4 project on “Measuring a common space and the dynamics of reform positions” within the DFG-funded Collaborative Research Centre (SFB) 884 “Political Economy of Reforms” (http://reforms.uni-mannheim.de) at the University of Mannheim. The topic of the PhD will focus on exploiting computational methods for analysing discourse phenomena like, e.g., uncertainty, vagueness and bias in political texts. This is a joint collaboration between the Natural Language Processing and Information Retrieval group (Prof. Simone Paolo Ponzetto) and the Chair of Artificial Intelligence (Prof. Heiner Stuckenschmidt), which will also involve close collaboration with project partners at the Department of Political Science (Prof. Dr. Nicole Rae Baerg, Prof. Dr. Thomas Gschwend), ranked as the best Political Science Department in Germany in different national and international university rankings. The student will be located at the Data and Web Science Group (DWS) of the University of Mannheim, one of leading centers for Data Science in Germany.

We are particularly interested in candidates with a background in one or several of the following areas:

  • statistical semantics and discourse processing
  • machine learning and natural language processing
  • discourse analysis
  • automated text-based scaling

Applicants should have a Masters degree (or obtain it in the near future) in Computer Science, Natural Language Processing, Machine Learning or Social Science and have previous experience in applying human language technology.

Duration: initially one year (starting in Fall 2015) with possible extension to 3-5 years. Salary range: according to German public scale TV-L 13 100% (full time, ranging between 3200,- and 4.600,- Euro before taxes depending on qualification).

Applications can be made per e-mail (sfb884@informatik.uni-mannheim.de) and should include a short research statement, CV, copy of university degrees and transcripts and - if available - a copy of the master thesis, as well as list of publications and published software. Further information about the groups can be found at http://dws.informatik.uni-mannheim.de/. All documents should be e-mailed as a single PDF. All applications sent before September, 15 2015 will receive full consideration. The positions remain open until filled.

The University of Mannheim is committed to increase the percentage of female scientists and encourages female applicants to apply. Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.

Please contact Simone Paolo Ponzetto (simone(At)informatik(DoT)uni-mannheim(DoT)de) and Heiner Stuckenschmidt (heiner(At)informatik(DoT)uni-mannheim(DoT)de) for informal enquiries.



Postdoctoral Fellow in NLP for EEG Analysis at Temple University

  • Employer: The Neural Engineering Data Consortium, College of Engineering, Temple University
  • Title: Postdoctoral Research Fellow
  • Topics: Natural Language Processing, Machine Learning, Big Data, EEG Analysis
  • Location: Philadelphia, PA
  • Deadline: Open until filled
  • Date Posted: August 12, 2015
  • Contact: Joseph Picone (joseph.picone@gmail.com)

Research focus: The Neural Engineering Data Consortium (NEDC) at Temple University invites applications for a Postdoctoral Fellow position in the area of automated EEG analysis. The Postdoctoral Fellow will contribute to a project that enables comparative research by automatically uncovering clinical knowledge from a vast BigData archive of clinical EEG signals and EEG reports collected over the past 14 years at Temple University Hospital (see www.isip.piconepress.com/projects/tuh_eeg for more information). We are developing a proof-of-concept based on the discovery of patient cohorts and provide an annotated BigData archive as well as the software that enabled the annotations and the generation of the patient cohort retrieval system. The candidate will be involved in overseeing the generation of labeled data for machine learning training, developing algorithms to automatically uncover and model structure based on deep learning principles, implementing an active learning approach that minimizes the amount of labeled data needed and supervising research to automatically extract medical concepts from EEG reports. A large portion of the project focuses in extraction of information from unstructured text, and hence, expertise in natural language processing is important.

Supervisor: Iyad Obeid, PhD and Joseph Picone, PhD

Required skills: The candidate’s primary expertise will be in natural language processing and/or computational linguistics. Proficiency in machine learning and big data techniques is highly desirable. Software engineering experience is also desired.

Education: A Ph.D. in computer science, computational linguistics, artificial intelligence or similar disciplines is required.

Length of appointment: This position is for three years.

Available: October 1, 2015.

Compensation: $42,000/year (NIH standard scale applies).

To apply: Send a CV and cover letter to joseph.picone@gmail.com (see http://www.isip.piconepress.com/images/memorabilia/temple/20150811_postdoc/postdoc_announcement_v00.pdf for more details)


Postdoctoral Fellow in Sentiment Analysis at McMaster University

  • Employer: Department of Linguistics, Department of Computing and Software, McMaster University
  • Title: Postdoctoral Research Fellow
  • Topics: Sentiment Analysis, Natural Language Processing
  • Location: Hamilton, ON, Canada
  • Deadline: Open until filled
  • Date Posted: July 24, 2015
  • Contact: Victor Kuperman (vickup@mcmaster.ca)

Research focus: Successful applicants will be working closely with a vibrant cross-faculty team of linguists, psychologists and computer scientists. The selected candidate will contribute to a research program that explores individual and group (gender, age) variability in perception and regulation of emotion. Primary responsibilities will include investigating new algorithmic techniques for identifying fine-grained sentiment on textual data, and semi-structured data, including social media. Equally important to the project is the development of lexical-semantic tools allowing big data analyses of text corpora for the purposes of text classification, topic modeling, development of semantic networks, and estimation of semantic similarity.

Supervisor: Victor Kuperman, PhD, Fei Chiang, PhD

Required skills: The candidate’s primary expertise will be in natural language processing, sentiment analysis, and/or computational linguistics. Proficiency in machine learning techniques is highly desirable.

Education: A Ph.D. in computer science, computational linguistics, artificial intelligence or similar disciplines is required.

Length of appointment: This position is for two years.

Available: August 1st, 2015.

Compensation: $50,000/year.

To apply: see application procedure at http://www.cas.mcmaster.ca/~fchiang/misc/postdoc.pdf


Postdoctoral Fellow in Natural Language Processing at Brigham and Women's Hospital / Harvard Medical School

  • Employer: Brigham and Women's Hospital / Harvard Medical School
  • Title: Postdoctoral Research Fellow
  • Topics: Natural Language Processing
  • Location: Boston, MA
  • Deadline: Open until filled
  • Date Posted: July 11, 2015
  • Contact: Alexander Turchin (aturchin@bwh.harvard.edu)

Research focus: the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of open-source natural language processing framework software and high-dimensional predictive models that utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.

Supervisor: Alexander Turchin, MD, MS, FACMI

Required skills: strong programming and system development skills; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills. Experience in programming in Perl and .NET and experience with natural language processing and medical terminologies / ontologies is a strong plus.

Education: PhD in computer science, biomedical informatics, linguistics, or related discipline, MD or an equivalent degree.

Length of appointment: This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.

Available: August 1st, 2015.

Compensation: according to NIH (NRSA) stipend levels.

To apply: send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.


Data Scientist - Unstructured Data at Civis Analytics

  • Employer: Civis Analytics
  • Title: Data Scientist - Unstructured Data
  • Topics: Natural Language Processing, Machine Learning, Deep Learning, Big Data Analytics, Computer Vision, Speech Processing, Algorithm Development
  • Location: Chicago, IL
  • Deadline: Open until filled
  • Date Posted: June 23, 2015
  • Apply Online: civisanalytics.com/careers
  • Questions: apply@civisanalytics.com


Who We Are

Civis Analytics is building a data-driven world. We create technologies that empower organizations to unlock the truth hiding in their own data—transforming them into smart organizations that are ready to thrive.

While our history is rooted in political campaign targeting, we’re now partnering with intelligent organizations in healthcare, media, education, and a range of other domains. We’re also building cloud-based products to do data science better.

We're solving the world's biggest problems with big data. Through research, experimentation, and iteration, we’re transforming how organizations do analytics. Our clients range in scale and focus from local to international, all empowered by our individual-level, data-driven approach.

Our incredible team of engineers, statisticians, researchers, and solution seekers come from all over the world with diverse backgrounds in Fortune 500 companies, international non-profits, Ivy League academia, and even actual rocket science.

Why should you join our team?

We are already hard at work on solving the world’s toughest problems with Big Data – working with organizations to analyze and understand their individual level data to improve outcomes and implement organizational change. We use cutting edge data science techniques, and we want to continue be on the forefront of innovation in our field.

We are smart, fun, and a little bit weird. Does this sound like you?

Position Overview

The Research and Development team is responsible for developing the fundamental data science methods, techniques, and best practices that power the mission of our company. Our diverse work includes predictive analytics, algorithm development, experimental design, visualization, and survey research.

As a Data Scientist on our Chicago-based Research and Development team, you will work closely and collaboratively with analysts and engineers to develop and operationalize the techniques that quantify and solve big, meaningful problems. Our team dives deeply into big problems and works in a variety of areas. With a specialization in unstructured data, this Data Scientist role will apply techniques from fields such as machine learning, applied statistics, natural language processing, computer vision, and speech processing to the growing unstructured datasets being collected at Civis. Because the majority of the world’s information is unstructured, being able to leverage these diverse and voluminous data sources adds tremendous value to Civis products and research. In this role, you will be a critical voice shaping both how unstructured data informs existing Civis products and services, and how it leads to the development of entirely new ways of serving our clients, novel to the industry as a whole.

We are looking for individuals from a diversity of backgrounds with demonstrated quantitative and problem-solving skills. We value creativity, hard work, and on-the-job-excellence and offer competitive compensation and benefits packages. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States.

Requirements

MINIMUM QUALIFICATIONS

  • Bachelor’s degree in a quantitative field, such as computer science, statistics, machine learning, or electrical engineering
  • Knowledge of and practical experience in applying the methodology of one or more unstructured data analysis fields, such as natural language processing, speech processing, or computer vision
  • Familiarity with statistical packages such as R, Stata, or in the Python scientific stack (NumPy, SciPy, scikit-learn, pandas)
  • Experience with common toolkits for unstructured data analysis, such as Theano, Torch, open-cv, the Stanford NLP tools, HTK, and Kaldi
  • Experience with SQL databases
  • Strong programming skills
  • Experience identifying and correcting for problems in imperfect data
  • An ability and eagerness to constantly learn and teach others

PREFERRED QUALIFICATIONS

  • Master’s degree in a quantitative field such as computer science, statistics, machine learning, or electrical engineering
  • Significant work experience in applying the methodology of one or more unstructured data analysis fields
  • High proficiency in programming with Python, Go, Java, Lua, C, or other languages used for high-performance statistical computing
  • Familiarity with architectures for scaling statistical computing to big data applications, such as Hadoop and Spark

How to Apply

Apply online at: civisanalytics.com/careers

Postdoctoral Fellow in NLP at University of Pennsylvania

  • Employer: Dept. of Computer and Information Science, University of Pennsylvania
  • Title: Postdoctoral Researcher
  • Topics: Natural Language Processing, Unsupervised Learning
  • Location: Philadelphia, PA
  • Deadline: Open until filled
  • Date Posted: June 19, 2015
  • Contact: Mitch Marcus (mitch@cis.upenn.edu)

Job Description

Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania. This is a full time position for 24 months, starting immediately.

The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora. The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years, and we intend to shamelessly exploit them all.

The candidate will work under the supervision of Profs. Mitch Marcus and Lyle Ungar in Computer and Information Science and Prof. Charles Yang in Linguistics.

Requirements

The candidate should have a very strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science with a good publication record. Experience in machine learning, good programming skills, and a good knowledge of modern linguistics are required.

How to Apply

Please email your CV and the names and contact information of three or more references to Mitch Marcus at the email provided above.


Postdoctoral Fellow in Machine Learning/Computational Linguistics for Child Language Acquisition

Job Description

We are recruiting for post-doctoral fellow to work on the application of machine learning/computational linguistic techniques to child language acquisition.

You should have a PhD in Computer Science/Engineering/Linguistics/Psychology and have experience with machine learning algorithms applied to language data and have published your work in conference proceedings or journals. Experience with auditory speech processing, deep learning, cloud computing, and GPU programming is desirable. The post is available for 2 years.

The computational community has developed a wealth of algorithms that can automatically discover linguistic units and dependencies between these units and these algorithms have been applied to language parsing and generation. In contrast, child language researchers often study child language using human coding of detailed linguistic information. The goal of this project is to develop a bridge between these two approaches. Machine learning techniques would give child language researchers ways to pull out relevant utterances that could be subject to greater processing. Child language analyses could be compiled into test sets that could be used to evaluate machine learning algorithms. In this post, you will develop machine learning algorithms for child language and also develop a web site that will enhance the ability of machine learning researchers and child language researcher to share data and algorithms. The research topics and approaches are open to negotiation. Children have some of the most advance language learning algorithms and understanding how they learn language could lead to new insights for computational approaches to language.

This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the new ESRC International Centre for Language and Communicative Development, a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster.

More information is available here: https://sites.google.com/site/sentenceproductionmodel/news

Postdoctoral Fellow and Software Engineer postions in biomedical natural language processing, machine learning and biomedical informatics

  • Employer: UMass Medical School Worcester
  • Title: Post-doctoral fellow or Software Engineer
  • Topics: Biomedical natural language processing, machine learning, bioinformatics, algorithm development, big data analytics
  • Deadline: until filled
  • Date Posted: 24 May 2015
  • apply by contacting elaine.freund@umassmed.edu

Job Description

We are recruiting for multiple positions at levels from Post Doctoral Fellow to Software Engineer to participate research and software development in biomedical natural language processing (NLP) and biomedical informatics. The group’s research (http://www.bio-nlp.org/index.php/projects) involves developing algorithms and tools for gathering, analyzing and interpreting heterogeneous data from multiple sources both clinically and research related. Recruits will lead development efforts in web service tools and search engines that: retrieve and summarize big data in biomedical domain, automatically extracting information from pdf files and extracting text from images, integrate novel biomedical text mining algorithms into the web tools and search engines to enable intelligent semantic search, and mining electronic health record data for pharmacovigilance.

If you are highly motivated and passionate about research in big data processing or software engineering or have in-depth knowledge and hands on implementation experience with web service tools and are interested in learning more about us, please contact elaine.freund@umassmed.edu with your resume or CV and a cover letter.

General Summary of Postdoc Fellow Position: PhD in Computer Science, computational linguistics or Biomedical Informatics with expertise in natural language processing, machine learning or information retrieval with excellent writing and communication skills and ability to work with the research team.

General Summary of Software Engineer Position: Under the direction of the Faculty or designee, the Software Engineer I assists with the design, development, implementation and integration of web service tools, search engines, utilities, applications and enhancements in a complex medical/academic research computing environment.

Research Scientist in natural language processing, machine learning, knowledge discovery, data analytics at IBM Research-Almaden

  • Employer: IBM Research
  • Title: Research Scientist
  • Topics: Nature language processing, information integration, entity resolution, machine learning, knowledge discovery, and data analytics
  • Location: San Jose, California, USA
  • Deadline: 1 June 2015
  • Date Posted: 6 May 2015
  • Online application: https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0751127

Job Description

IBM Research - Almaden is looking for researchers to join the Natural Language Processing (NLP), Entity Resolution and Discovery (NERD) Department. Our research focuses include high-value content creation from variety of public and third-party data sources, scalable and usable analytics tools for individual stages in analyzing such data sources, such as text analytics, entity resolution, large-scale machine learning, techniques and methods for scalable and flexible indexing and querying support over enriched content, and consumable interfaces for accessing such data sources, including natural language interfaces. An example project is SystemT (http://ibm.co/1Cdm1Mj).

We are currently looking for a Research Staff Member to conduct research with large scale real-world heterogeneous data in the area of advanced analytics, such as nature language processing, information integration, entity resolution, machine learning, knowledge discovery, and data analytics. This role generates highly novel ideas, both theoretical and experimental, in a specific engineering or scientific discipline and invents and designs complex products and processes. This position may be involved in engineering these ideas to an advanced state of feasibility by evaluating ideas and plans and participating in their design and development. The full cycle of innovation to delivery is typically a multiple-year effort.

The candidate is also responsible for internally and externally disseminating the results of such activities through publications, patent disclosures, seminar participation, technical documentation, etc. The candidate represents IBM at professional conferences, in professional societies and universities and functions as an internal consultant in the areas of professional expertise.

Required

  • Master's Degree
  • At least 1 year experience in developing advances in Computer Science disciplines
  • At least 1 year experience in performing Scientific Research
  • English: Intermediate

Preferred

  • Doctorate Degree in Information Technology
  • At least 3 years experience in developing advances in Computer Science disciplines
  • At least 3 years experience in performing Scientific Research
  • English : Fluent

Additional Information

The World is Our Laboratory: No matter where discovery takes place, IBM researchers push the boundaries of science, technology and business to make the world work better. IBM Research is a global community of forward-thinkers working towards a common goal: progress.

IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.


PhD position in statistical language modelling

  • Employer: Cardiff University
  • Title: PhD scholarship
  • Topics: Statistical language modelling, relation extraction, social media
  • Location: Cardiff, UK
  • Deadline: 1 June 2015
  • Date Posted: 7 April 2015
  • Online application: http://courses.cardiff.ac.uk/funding/R2497.html

Job Description

Applications are invited for a PhD Scholarship at the Cardiff School of Computer Science & Informatics in the area of statistical language modelling. Specifically, the aim of the project will be to develop methods for modelling the meaning of natural language terms, based on data from social media and other web sources. For example, by analysing the tags associated with Flickr photos, the developed methods will be able to learn that a church is a kind of building, that churches tend to be larger than typical buildings and that chapels are similar to churches. The results of this project will be used to improve methods from artificial intelligence for commonsense reasoning, and will among others enable more intelligent web search engines.

Funding and eligibility

This studentship consists of full UK/EU tuition fees, as well as a Doctoral Stipend matching UK Research Council National Minimum (£14,057 p.a. for 2015/16, updated each year). This studentship is open to students of any nationality. Students classified as international for fee purposes have to self-fund the difference between home and international fees.

Candidates should:

  • either have (or expect to have by Autumn 2015) a good honours degree in a relevant discipline (minimum 2:1);
  • or have a masters degree with distinction in the research dissertation in a relevant discipline;
  • or have professional qualifications deemed by Cardiff University to be equivalent to the above;
  • or be over 25 and have relevant work experience in a position of responsibility.

The methods will rely heavily on methods from statistics and linear algebra, hence a strong background in mathematics will be required, in addition to excellent programming skills. A strong mathematical background and excellent programming skills will also be required.

Applicants are particularly welcomed from candidates with a background in computer science.

If your first language is not English you must provide evidence of competence in English. Our standard requirement is an overall IELTS result of at least 6.5, with a minimum of 6.5 in writing, and a minimum of 6.0 in speaking, listening and reading.

Further information

For further information and instructions on how to apply, please see http://courses.cardiff.ac.uk/funding/R2497.html

Postdoctoral Researcher in NLP at U.S. Army Research Lab

  • Employer: U.S. Army Research Lab, Adelphi Laboratory Center
  • Title: Postdoctoral Researcher
  • Topics: Natural Language Processing
  • Location: Adelphi, MD, USA
  • Deadline: Open until filled
  • Date Posted: March 17, 2015
  • Contact: Dr. Stephen Tratz (stephen.c.tratz.civ@mail.mil)

Job Description

The Multilingual Computing Branch (MLCB) at the U.S. Army Research Laboratory's Adelphi Laboratory Center, located in the Washington, D.C. metro area, is seeking to hire new post-doctoral fellows. MLCB has several ongoing efforts in computational linguistics/natural language processing, including active projects in machine translation, human-robot communication, and social media analysis. The branch is also pursuing new interdisciplinary initiatives to address the language processing challenges in cyber-security and video analytics.

Candidates should have substantial research experience in machine learning methods (e.g., deep neural networks) as applied to emerging areas involving computational linguistics. Areas of interest include: text/video analytics, computational social science, machine translation, domain adaptation, data selection, low-resource language processing, morphologically complex languages, knowledge representation and reasoning, spoken language interfaces and dialogue, and multimedia processing.

The lab encourages external collaboration and maintains multiple partnerships with universities and research institutions, which enable faculty and student exchanges as well as joint research and publishing (http://www.arl.army.mil/www/default.cfm?page=93). ARL’s new open campus initiative is attracting national and international partners from academia and industry to work with ARL scientists and engineers in areas of common research interest (see http://www.arl.army.mil/www/default.cfm?page=2357), and ARL researchers have begun releasing open source code via GitHub (see http://www.army.mil/article/141734/Army_cyber_defenders_open_source_code_in_new_GitHub_project/). ARL facilities include multiple high-end supercomputing clusters with over 10,000 cores and capable of at least 350 TFlops.

Requirements

  • Ph.D. or equivalent research experience in computer science, statistics, mathematics, or related field

How to Apply

If interested, please email your CV and the names and contact information of three or more references to Dr. Stephen Tratz at the email provided above.

Postdoctoral Researcher in NLG for Narrative

  • Employer: Liquid Narrative Group, North Carolina State University
  • Title: Postdoctoral Research Scholar
  • Topics: Natural Language Generation, Narrative Generation, Knowledge Representation, AI Planning
  • Location: Raleigh NC, USA
  • Deadline: Open Until Filled
  • Date Posted: March 10, 2015
  • Online Application: http://jobs.ncsu.edu/postings/40524

Job Description

The Liquid Narrative group at North Carolina State University is seeking a postdoctoral researcher to collaborate on a large-scale narrative generation project. The goal of this project is to build computational tools for the use of narrative in sense-making tasks. Research thrusts include the creation of formalisms for representing story and discourse knowledge and the development of narrative generation algorithms able to create multiple narrative discourses from a given story, adapt these discourses to an audience, and elicit different effects such as surprise or suspense. This project aims at creating a large-scale narrative-generation system that can extract story data from various sources (e.g., video game logs) and create narratives in and across several media such as text, animated movies or maps.

The postdoctoral researcher will contribute to the design and development of narrative generation and summarization technologies, focusing on the microplanning aspect of text generation. In particular, he or she will extend an existing narrative discourse generation prototype that outputs basic sentences using the SimpleNLG library. Our aim is to update this architecture by integrating an NLG system such as FUF/Surge, KPML or RealPro. To improve the quality of the generated text, the postdoctoral researcher will work on topics such as: aggregation, generation of referring expressions, discourse markers insertion, lexical choice and/or other aspects of realization that are specific to narrative as a genre.

He/she may also participate in research efforts on the automated generation of multimedia presentations involving text, video and maps. He/she is expected to collaborate in performing scientific evaluations of the systems, and in writing academic research papers.

Requirements

The applicant must hold a PhD degree, preferably in the area of computational linguistics or natural language generation. He/she should have:

  • Experience with developing NLG systems
  • Excellent software-design and problem-solving skills
  • Good programming skills
  • Excellent written and oral communication skills

Experience in the following areas would be a plus:

  • Automated discourse planning technologies
  • Dialogue generation

Position details

This is a full-time position. Expected start date is April 1, 2015 and the initial funding for the position runs through December 31, 2015. The position may be extendable depending on availability of funds.

Interested candidates should view the official Human Resources posting and submit applications through the NC State University HR web page at http://jobs.ncsu.edu/postings/40524

NC State University is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, gender identity, age, sexual orientation, genetic information, status as an individual with a disability, or status as a protected veteran. Individuals with disabilities requiring disability-related accommodations in the application and interview process, please call 919-515-3148.


PhD-level Researchers in Language Technology or Computational Linguistics

  • Employer: UKP Lab, Technische Universität Darmstadt (Germany)
  • Title: PhD-level Researchers in Language Technology or Computational Linguistics
  • Topics: Natural Language Processing, Summarization, Opinion Mining
  • Location: Darmstadt (Germany)
  • Deadline: open until the position is filled
  • Date Posted: March 4, 2015
  • Contact: Prof. Iryna Gurevych apply-for-aiphes(a-t)ukp.informatik.tu-darmstadt.de

Job Description

The newly established Research Training Group „Adaptive Information Processing of Heterogeneous Content“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht-Karls-University Heidelberg is filling several positions for three years, starting as soon as possible:

PhD-level Researchers in Language Technology or Computational Linguistics

The positions provide the opportunity to obtain a doctoral degree with an emphasis within one of the following guiding themes:

  • A3: Opinion and Sentiment - extrapropositional aspects of discourse (Univ. of Heidelberg)
  • B1: Structured summaries of complex contents (TU Darmstadt)
  • B2: Content selection based on linked lexical resources (TU Darmstadt)
  • D1: Multi-level models of information quality in online scenarios (TU Darmstadt)
  • D2: Manual and Automatic Quality Assessment of Summaries from Heterogeneous Sources (TU Darmstadt)

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 on multi-document summarization in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment will be developed. AIPHES will investigate a novel summarization scenario for information preparation from heterogeneous sources. There will be close interaction 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 the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann), Multimedia Communications (Dr. Rensing). Participants at the Ruprecht-Karls-University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media.

AIPHES will emphasize close contact between students and their advisors, have 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.

Requirements

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 able 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. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht-Karls-University Heidelberg is one of the large 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 of the above listed guiding themes,
  • 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.

They should be submitted until March 23th, 2015 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address apply-for-aiphes(a-t)ukp.informatik.tu-darmstadt.de. The interviews may start any time. The positions are open until filled.


Research staff position in Natural Language Processing

  • Employer: UKP Lab, Technische Universität Darmstadt (Germany)
  • Title: Research staff position in Natural Language Processing
  • Topics: Natural Language Processing, Question Answering
  • Location: Darmstadt (Germany)
  • Deadline: open until the position is filled
  • Date Posted: March 4, 2015
  • Contact: Nicolai Erbs erbs@ukp.informatik.tu-darmstadt.de

Job Description

The Ubiquitous Knowledge Processing Lab (UKP Lab) at the Department of Computer Science of the Technische Universität (TU) Darmstadt, Germany, has an opening for a research staff position (TV-TU E13 German payscale) with a focus on question answering and summarization of social media content. This DFG-funded basic research project conducts research integrating semantic text analysis, such as semantic role labeling (SRL), into higher-level applications in information access to improve their overall results (Principal Investigator: Prof. Dr. Iryna Gurevych). Thereby, we pay special attention to graph-based techniques.

The selected candidate will work with a large corpus from a social question-answer platform on the Web. He/she will be expected to identify interesting research problems, research ways of utilizing semantic role labeling in novel NLP tasks, and develop means and resources to evaluate the results. The newly established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG [3] provides an excellent research environment for this kind of work. The funding is available for the duration of at least two years with an option for extension.

Requirements

We ask for applications from applicants in Computer Science or Computational Linguistics, preferably with completed PhD and research publications. Experience in Question Answering or a related field like summarization or information retrieval is a definite advantage. Excellent graduates of these disciplines willing to work towards a PhD are also encouraged to apply. Ideally, the candidates should have strong research skills as well as demonstrable experience in designing and implementing complex natural language processing (NLP) applications in Java and/or with graph-based algorithms. A very good command of German is a definite plus, since the target corpus is in the German language. Excellent communication skills in English and the ability to work in a team are required.

Applications should include a CV, a motivation letter, an outline of research experience, as well as names and addresses of two referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: erbs@ukp.informatik.tu-darmstadt.de by 23.03.2015. The position is open until filled.


PhD-position in NLP/Text Mining

  • Employer: UKP Lab, Technische Universität Darmstadt (Germany)
  • Title: PhD-position in NLP/Text Mining
  • Natural Language Processing, Text Mining
  • Location: Darmstadt (Germany)
  • Deadline: open until the position is filled
  • Date Posted: March 4, 2015
  • Contact: Richard Eckart de Castilho (eckart (at) ukp (dot) informatik (dot) tu-darmstadt (dot) de)

Job Description

The Ubiquitous Knowledge Processing Lab (UKP Lab) at the Department of Computer Science of the Technische Universität (TU) Darmstadt, Germany, has an opening for a PhD student (TV-TU E13 German payscale) in a research project in Natural Language Processing (NLP) for a computer scientist or computational linguist. The project focusses on building an open text-mining infrastructure at the European level (Principal Investigator: Prof. Dr. Iryna Gurevych).

Thereby, major NLP and Text Mining platforms, including UIMA and GATE, should be made interoperable and applied to knowledge discovery in scientific literature, e.g. entity disambiguation and linking to a background knowledge repository. In the past, the UKP Lab has developed several frameworks such as the Darmstadt Knowledge Processing Repository (DKPro) and UBY. They form the foundation for the research and implementation work to be done. The graduate program Knowledge Discovery in Scientific Literature provides further research environment for the work to be carried out.

Requirements

Applicants in Computer Science or Computational Linguistics must have demonstrable experience in designing and implementing complex natural language processing (NLP) systems or NLP-based applications and the programming language Java as well as strong research skills. Excellent communication skills in English and the ability to work in a team are required. Experience in open-source software development is a plus.

The following academic qualification is necessary: completion of an M.A./M.Sc. in Computer Science, Computational Linguistics, or a related field.

Pending the successful completion of the ongoing administrative steps for the project, funding of this position is available from June 1st, 2015 for the duration of three years.

Applications should include a CV, a motivation letter, an outline of research experience, as well as names and addresses of two referees.

Interviews may start at any time and will continue until the position has been filled. Email address for inquiries and applications: eckart (at) ukp (dot) informatik (dot) tu-darmstadt (dot) de

The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. The UKP Lab is also home to the unique research initiative "Knowledge Discovery in the Web” which emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge.

The Technische Universität Darmstadt promotes gender equality and in particular encourages women to apply. Preference will be given to physically handicapped persons if they are equally qualified.

Postdoc in Advanced Machine Learning (with an Emphasis on NLP)

Job Description

The Computer Science Department at the University of Notre Dame in collaboration with the Institute for Intelligent Systems at the University of Memphis anticipates hiring a postdoctoral fellow starting as early as April 1st 2015 for one year and renewable for a second year. The position includes a full time salary and benefits and is jointly funded by sponsored research split between the University of Notre Dame and the University of Memphis. Review of applications will start immediately and continue until the position is filled.

The successful candidate will conduct research in machine learning applied to dialog-centered natural language understanding. He/she will participate in the development and application of machine learning techniques in the hierarchical and temporal domains to multi-party speech data collected in authentic educational contexts.

The candidate will work under the supervision of Dr. Sidney D’Mello, who has joint appointments in the Departments of Computer Science and Psychology at Notre Dame, and Dr. Andrew Olney in the Institute for Intelligent Systems at the University of Memphis.

The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within a multi-department multi-institution grant-funded project. The postdoc will be encouraged to build advanced technical skills, strengthen their research portfolios via peer-reviewed publications, develop leadership skills by mentoring students, and gain expertise in authoring collaborative grant proposals.

Required

(1) Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire; (2) Research experience in advanced machine learning techniques for sequential and hierarchical domains (e.g., probabilistic graphical models, sequence tagging, deep learning) ; (3) Evidence of a strong publication record in the aforementioned areas

Desired

(1) Research experience in one or more of the following research areas (acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling) ; (2) Experience working on interdisciplinary projects and/or on educational research; (3) Experience mentoring graduate and undergraduate students

For more information see the application link above.

Software Engineer/NLG Specialist in Sydney, Aus - Natural Lanaguage Generation

Job Description

  • Unique opportunity within the Equities Research space for a Engineer with strong NLG experience
  • New Systems Implementation with Opportunity to push the envelope within Research
  • Permanent Opportunity – Sydney CBD Location

About the role

We are seeking a Software Engineer to join our Equities Research business team. This is a truly unique opportunity for someone to join Macquarie working on a pioneering project within the business which could be a big game changer. The role will utilise your strong NLG/NLP experience and you will be responsible for building and developing the NLG functionality within the team. If you are interested in gaining commercial experience with NLG, have excellent written communications and have a flair for English grammar, have a passion for finance and in particular Equities Trading and want the opportunity to really pioneer something, then this could be the position for you.

Key Responsibilities

  • Design and Develop our first NLG/NLP Application within Equities Research
  • Work closely with the vendor to understand the application limitations and functionality
  • Drive the development with the Head of Research as well as industry analysts
  • Mature the offering and look for further areas of development within the business

About You

To be successful in this role as a Software Engineer you will possess a University Degree in Computer Science/Mathematics and would have probably undertaken further studies of some sort (Masters/PhD) and have previous Natural Language Generation/Processing experience in either a commercial or research environment. You will have a passion and flair for the English Language as well as having a interest in financial services and in particular traded products. Previous OO Development experience would be highly regarded. In addition you will possess the following:

  • Tenacity to produce different If Statements and to develop the platform further
  • Strong interest in Artificial Intelligence/Machine Based Learning.
  • Keen interest in finance
  • Self Starter and strong attention to detail to really drive uptake of the platform

This is a unique opportunity within Macquarie and quite possibly a pioneering project within the Investment Banking space. We are looking to hire two developers into the team and are flexible across career levels from recent Grads to Senior Engineers. Here at Macquarie we truly believe in you owning your future, at Macquarie you’ll own it. Find out more at the new Careers website: macquarie.com/career

If you meet the above requirements, please apply via the following link. Alternatively to find out more about the position and a confidential discussion, please contact Andy Logan on 02 8237 8472 or andy.logan@macquarie.com

PostDoc Position in Heidelberg (NLP, Networks, Databases, Machine Learning)

  • Employer: Heidelberg Institute for Theoretical Studies gGmbH (HITS)
  • Title: PostDoc
  • Specialties: Natural Language Processing, Networks, Databases, Machine Learning
  • Location: Heidelberg, Germany
  • Deadline: 20 February 2015
  • Date posted: 29 January 2015
  • Contact information: michael.strube (at) h-its.org
  • Online application: https://application.h-its.org/intern/register.php?id=o51kdq1

Job Description PostDoc position available in the NLP group at the Heidelberg Institute for Theoretical Studies (HITS) in Heidelberg, Germany

One position is available for a PostDoc working in Natural Language Processing, in particular in the areas of Entity Linking, Cross-document Coreference Resolution, Coreference Resolution, Word Sense Disambiguation. The position is within a newly funded project on "Scalable Author Name Disambiguation in Bibliographic Databases". Project partners are DBLP (http://dblp.org/db/) and zbMATH (https://zbmath.org/), the two leading bibliographic databases in computer science and mathematics which will also supply the data to be disambiguated and the gold standard. The project will be funded for three years starting June 1st, 2015.

The candidate should have a strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science. Experience with machine learning, databases, parallel programming, big data and networks as well as strong programming skills are required.

HITS gGmbH is a private non-profit research institute carrying out multidisciplinary research in the computational sciences. It receives its base funding from the HITS Stiftung.

The NLP group (http://www.h-its.org/en/research/nlp/) at HITS is an interdisciplinary research group that works on applications in the area of discourse and dialogue, in particular coreference resolution, entity linking, automatic summarization, and knowledge extraction from semistructured input. The NLP group at HITS works closely together with the Computational Linguistics Department at the University of Heidelberg.

To apply, please enter your application via the following link: https://application.h-its.org/intern/register.php?id=o51kdq1 (reference Postdoc NLP HITS-01-2015)

Applications must be submitted by February 20, 2015. Please note that applications not submitted via the online system will not be considered. Inquiries about the position can be directed at Michael Strube (michael.strube (at) h-its.org).


Postdoc position in Cardiff (NLP, IR, machine learning)

  • Employer: Cardiff University
  • Title: Postdoc
  • Specialties: Natural language processing, information retrieval, machine learning, distributional models, relation extraction, commonsense resoning
  • Location: Cardiff, UK
  • Deadline: 3 February 2015
  • Date posted: 9 January 2015
  • Contact information: SchockaertS1@cardiff.ac.uk

Job Description

Applications are invited for a postdoctoral research associate post in the School of Computer Science & Informatics at Cardiff University. This is a full-time, fixed-term post for 30 months, starting on 1 May 2015 or as soon as possible thereafter.

The main aim of this project is to learn fine-grained semantic relations from large text corpora. Initially such relations will be obtained in an unsupervised way, by identifying semantic relations with spatial relations between vector-space representations. Subsequently, open-domain, supervised relation extraction methods will be developed which use the output of the unsupervised methods as training data. This research will be part of an ERC funded project on the use of semantic relations between natural language terms in logics for commonsense reasoning. You will work closely with Dr Steven Schockaert. You will possess a PhD in Computer Science or a closely related area, or have equivalent experience.

Essential criteria

  • Proven ability to undertake research in a relevant research area (e.g. natural language processing, information retrieval, machine learning) at an international level, as evidenced by research output.
  • Excellent programming skills (java or C/C++).
  • A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, SIGIR, CIKM, IJCAI, AAAI, ICML) and journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, ACM Trans. Information Systems, IEEE Trans. Knowledge and Data Engineering).
  • Proven ability to communicate specialist ideas clearly in English using written media.
  • Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.
  • A PhD in Computer Science or closely related area, or equivalent experience.

Desirable criteria

  • Knowledge of statistical natural language processing.
  • Knowledge of unsupervised and semi-supervised learning.
  • Knowledge of relation extraction.
  • Experience with analysing large text corpora using a high-performance computing environment.
  • Experience with dimensionality reduction methods such as multi-dimensional scaling, singular-value decomposition, and non-negative matrix factorisation.

More information For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 2972BR.

Post‐Doctoral and all levels of Research Scientist at the Allen Institute for Artificial Intelligence

  • Employer: Allen Institute for Artificial Intelligence (AI2)
  • Title: Post-doc/Research Scientist
  • Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation
  • Location: Seattle, WA
  • Deadline: N/A, we are hiring throughout 2015
  • Date posted: 12/9/2014
  • Contact information: ai2-info@allenai.org, allenai.org

Job Description

The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Post Docs and Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities.

Position Summary

AI2 currently has projects in the following areas:

  • Language and Vision
  • Information extraction and semantic parsing
  • Question answering
  • Language and reasoning
  • Machine learning and theory formation
  • Semantic search
  • Diagram understanding

AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting the research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations.

Applicant

Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, or question answering and explanation. We look favorably upon extensive work experience demonstrating application of your research.

Application Process

All candidates are required to submit a resume, an expression of interest, and the names and contact information of at least 2 references (including email addresses) through our website: http://allenai.github.io/ai2website/jobs.html. We particularly welcome applications from women, people of color, members of the LGBT communities, and people with disabilities. Visa sponsorship is available.


Multiple Tenure-Track Positions (w/focus in Data Analytics) at The Ohio State University Department of Computer Science and Engineering

  • Employer: The Ohio State University
  • Title: Assistant/Associate/Full Professor
  • Specialty: open, two positions in Data Analytics
  • Location: Columbus, OH, USA
  • Deadline: January 31, 2015 (Consideration starts November 2014)
  • Date Posted: November 17, 2014
  • Website: https://web.cse.ohio-state.edu/cgi-bin/portal/fsearch/apply.cgi

The Computer Science and Engineering Department at the Ohio State University expects to fill multiple tenure-track positions and seeks applicants in all areas of computer science.

Particular emphasis will be placed on filling two open rank positions in conjunction with a broad university-wide research initiative on Data Analytics (https://discovery.osu.edu/focus-areas/data-analytics/collaborative.html), and a recently announced undergraduate program in Data Analytics (https://data-analytics.osu.edu). Areas of interest for these positions include (but are not limited to): data mining, big data management, cloud computing systems, data analytics; application of machine learning or data mining or data visualization to problems in network science (including social networks), health, and climate science.

The department is committed to enhancing faculty diversity; women, minorities, and individuals with disabilities are especially encouraged to apply.

Applicants should hold or be completing a Ph.D. in CSE or a closely related field, have a commitment to and demonstrated record of excellence in research, and a commitment to excellence in teaching.

To apply, please submit your application via the online database. The link can be found at: https://web.cse.ohio-state.edu/cgi-bin/portal/fsearch/apply.cgi.

Review of applications will begin in November 2014 and will continue until the positions are filled.

The Ohio State University is an Equal Opportunity/Affirmative Action Employer.

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