Employment opportunities, postdoctoral positions, summer jobs

From ACL Wiki
Revision as of 11:22, 13 March 2017 by Gmflash (talk | contribs)
Jump to navigation Jump to search

Researcher in Machine Learning and NLP, DFKI, Germany

  • Employer: DFKI GmbH, Germany
  • Title: Researcher
  • Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation
  • Location: Saarbruecken
  • Deadline: March 31, 2017
  • Date posted: March 13, 2017
  • Contact: Prof. Josef van Genabith

The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.

Key research responsibilities include:

  • machine and deep learning for natural language processing/machine translation
  • software development and integration
  • publication in top-tier conferences and journals

General responsibilities include:

  • engagement with industry partners and contract research
  • identification of funding opportunities and engagement in proposal writing
  • contribution to teaching and supervision in accordance with University and DFKI rules and regulations
  • administrative work associated with programmes of research

Requirements:

  • MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar
  • Strong background and track record in machine learning, neural nets and deep learning
  • Strong background and track record in NLP and MT - Excellent programming skills
  • Excellent problem solving skills, independent and creative thinking
  • Excellent team working and communication skills
  • Excellent command of written and oral English
  • Command of German and other languages not a requirement but helpful

The successful applicant will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).

Working environment: DFKI is one of the largest AI research institutes worldwide, with several sites in Germany, covering basic research and applications. DFKI is a not-for-profit company with more than 500 researchers from 60+ countries across the globe. DFKI is based on a shareholder model including globally operating companies such as Intel, Google, Microsoft, Nuance, SAP, BMW, VW, Bosch, Deutsche Telekom, several SMEs, three German universities and three German Federal States.

The DFKI Multilingual Technologies lab partners in international, national and industry funded research projects in all areas of Language Technologies (including machine translation, question answering, information extraction, human-robot communication, speech and the multi-lingual web). The MLT lab currently leads the H2020 European Research project QT21 on MT, the EU CEF funded ELRC project and the EU funded TRADR project on human-robot collaboration in disaster response scenarios.

The MLT lab is part of the DFKI site at the Saarland University campus in Saarbrücken, Germany. Saarland University has exceptionally strong Computer Science and Computational Linguistics departments, two Max Plank Institutes in Computer Science, an Excellence Cluster in Multimodal Computing and Interaction and several International Doctoral and Master programmes in Computer Science and Computational Linguistics. DFKI staff regularly engage in teaching and supervision at Saarland University.

Geographical environment: Saarbrücken is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.

Starting date, duration, salary: Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.

Application: Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to Prof. Josef van Genabith referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact Prof. van Genabith for informal inquiries.


Associate Research Scientist, UKP Lab, TU Darmstadt

  • Employer: UKP Lab, Technische Universität Darmstadt, Germany
  • Title: Associate Research Scientist
  • Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning
  • Location: Darmstadt
  • Deadline: March 8, 2017
  • Date posted: February 21, 2017
  • Contact: Prof. Iryna Gurevych

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

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

to strengthen the group’s profile in the areas of Interactive Machine Learning (IML) or Natural Language Processing for Language Learning. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Interactive Machine Learning and Natural Language Processing for Language Learning are the focus areas researched in collaboration with partners in research and industry.

We ask for applications from candidates in Computer Science with a specialization in Machine Learning or Natural Language Processing, preferably with expertise in research and development projects, and strong communication skills in English and German.

  • The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes.
  • The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems.

Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP and/or ML) systems, experience in large-scale data analysis, large-scale knowledge bases, and strong programming skills incl. Java. Experience with neural network architectures and a sense for user experience design are a strong plus. Combining fundamental NLP research on Interactive Machine Learning or Natural Language Processing with practical applications in different domains including education will be highly encouraged.

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

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

Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the applications to: jobs@ukp.informatik.tu-darmstadt.de by 08.03.2017. The positions are open until filled. Later applications may be considered if the position is still open.

Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University

  • Employer: Northwestern University, USA
  • Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University
  • Speciality: Open area
  • Location: Evanston, IL, USA
  • Deadline: April 1, 2017
  • Date posted: February 17, 2017
  • Contact: matt-goldrick@northwestern.edu

The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).

The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.

To receive fullest consideration, applications should arrive by April 1, 2017. 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 that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.

E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (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.

Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK

  • Employer: Cardiff University, UK
  • Title: Research Associate in Artificial Intelligence / Machine Learning
  • Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models
  • Location: Cardiff, UK
  • Deadline: March 2, 2017
  • Date posted: February 13, 2017
  • Contact: schockaerts1@cardiff.ac.uk

Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience.

This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)

Essential criteria

  • Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience
  • An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.
  • A strong background in statistics and linear algebra.
  • Excellent programming skills.
  • Knowledge of current status of research in specialist field.
  • Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP).
  • Ability to understand and apply for competitive research funding.
  • Proven ability in effective and persuasive communication.
  • Ability to supervise the work of others to focus team efforts and motivate individuals.
  • Proven ability to demonstrate creativity, innovation and team-working within work.

Background about the university

Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework.

Background about the project

Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications.

The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.

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 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.

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

  • Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
  • Title: Research Associates in Natural Language Processing / Text Mining
  • Speciality: Natural Language Processing, Text Mining
  • Location: Manchester, UK
  • Deadline: March 13, 2017
  • Date posted: February 10, 2017
  • Contact: sophia.ananiadou@manchester.ac.uk

The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.

They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning.

Skills

You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java.

  • Duration of post: Immediately until 31st October 2018
  • Salary: £31,076-£38,183 per annum

Research Team

The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.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”.

Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).

Deadline of applications: 13/03/2017

Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975


Research Scientist Intern at Adobe Research, San Jose, California

  • Employer: Adobe Systems Incorporated
  • Title: Research Scientist Intern
  • Speciality: NLP, machine learning and dialog.
  • Location: San Jose, CA, USA
  • Deadline: March 1, 2017
  • Date posted: January 23, 2017
  • Contact: bui@adobe.com

We are looking for PhD students with background in NLP, machine learning, dialog to work on 2 following projects: 1) Deep reinforcement learning for creative assistant 2) Reading order text extraction for PDF documents

Assistant/Associate Professor Position in NLP/IR/Text/ML at University of California - Davis

  • Employer: University of California - Davis
  • Title: Assistant/Associate Professor
  • Speciality: All areas of NLP/Text/IR/ML etc including those involved in multi-media analysis.
  • Location: Davis, CA, USA
  • Deadline: January 2, 2017
  • Date posted: December 27, 2016
  • Contact: davidson@cs.ucdavis.edu

The Department of Computer Science at the University of California at Davis invites applications for a faculty position at the rank of Assistant or Associate Professor in Computer Science, for appointments with a start date in Spring 2017, or later. We are targeting excellent candidates in all areas of machine learning and computational linguistics, with a special emphasis on all aspects of natural language processing, information retrieval, text analytics and text mining. The campus is especially interested in candidates who can contribute to the diversity and excellence of the academic community through their research, teaching, and service.

Applications received by 2nd January 2017 will receive full consideration. For further information see http://www.cs.ucdavis.edu/blog/faculty-employment-positions-2/



Postdoctoral Fellow in Natural Language Processing / Machine Learning 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, Machine Learning, Predictive Modeling
  • Location: Boston, MA
  • Deadline: Open until filled
  • Date Posted: December 23, 2016
  • 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 led by Dr. Leonid Perlovsky (http://www.leonid-perlovsky.com/) and Dr. Alexander Turchin (https://connects.catalyst.harvard.edu/Profiles/display/Person/14588) on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.

Supervisor: Alexander Turchin, MD, MS, FACMI; Leonid Perlovsky, PhD

Required skills: strong mathematical background in statistics and machine learning; experience working with large datasets; experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with predictive modeling, medical terminologies / ontologies, python, MATLAB and Apache Spark is a strong plus.

Education: PhD in computer science, biomedical informatics, or related discipline 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: Immediately.

Compensation: according to NIH (NRSA) stipend levels (https://grants.nih.gov/grants/guide/notice-files/NOT-OD-16-131.html).

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


PhD Scholarship / Enhancing Scientific Text Summarization / Barcelona

  • Title: PhD Scholarship / Enhancing Scientific Text Summarization with Academic Social Networks
  • Location: Barcelona, Spain
  • Deadline: February 2nd, 2017
  • Date posted: December 12, 2016
  • Contact: horacio.saggion@upf.edu

In the context of the Marie-Curie PhD InPhiNIT La Caixa program associated to the Maria de Maeztu Strategic Research Program, we are looking for a highly motivated PhD candidate in the area of Natural Language Processing to work in a project dealing with Scientific Text Summarization and Academic Social Networks.

The PhD will be carried out at the TALN research group of the Department of Information and Communication Technologies (DTIC), Universitat Pompeu Fabra (UPF) in Barcelona.

The PhD student should have background in Natural Language Processing with a solid knowledge of statistics, mathematics, computer programming and machine learning. Experience in Information Extraction, Text Summarization, or related areas would be appreciated.

Brief description of the project:

http://www.dtic.upf.edu/~hsaggion/scientific_summarization_social.html

How and where to apply (InPhiNIT program):

https://obrasociallacaixa.org/en/educacion-becas/becas-de-posgrado/inphinit/programme-description


The TALN research group:

http://taln.upf.edu/

Maria de Maeztu Strategic Research at DTIC:

https://www.upf.edu/web/mdm-dtic/description

http://ec.europa.eu/research/mariecurieactions/

Other:

You can contact Prof. Horacio Saggion for more information about the project.

Related information:

https://www.upf.edu/web/mdm-dtic/projects/-/asset_publisher/Ef1was9TxNY4/content/id/4113025#.WE6ZIH23nm4

http://taln.upf.edu/pages/coling2016tutorial/





Lecturer/Senior Lecturer openings in Artificial Intelligence and Machine Learning at Imperial College London, UK

  • Employer: Department of Computing, Imperial College London
  • Title: Lecturer/Senior Lecturer openings in Artificial Intelligence and Machine Learning
  • Speciality: Artificial Intelligence and Machine Learning, including (but is not limited to): machine learning for text and speech.
  • Location: London, UK
  • Deadline: January 16, 2017
  • Date posted: December 8, 2016
  • Contact: margaret.hall@imperial.ac.uk

The Department of Computing at Imperial College London invites applications for full-time faculty members at the Lecturer/Senior Lecturer level (comparable to American tenure-track Assistant Professorships) who can contribute to research and teaching, in particular in the area of Artificial Intelligence and Machine Learning. This includes (but is not limited to): autonomous systems; knowledge representation and reasoning; planning; machine learning for speech, audio and text; optimization and data mining.

Notwithstanding the above focus, exceptional candidates from any area of Computer Science are also encouraged to apply.

The deadline for applications is 16th January 2017. For further information see http://www.imperial.ac.uk/computing/job-vacancies/


Research Fellow in Biomedical Text Mining, University of Manchester, UK

  • Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
  • Title: Research Fellow
  • Speciality: Natural Language Processing, Text Mining
  • Location: Manchester, UK
  • Deadline: December 18, 2016
  • Date posted: November 28, 2016
  • Contact: sophia.ananiadou@manchester.ac.uk

Applications are invited for a postdoctoral research fellow in Text Mining at the National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester. The position is for 2 years.

The objective of this BBSRC funded post is to conduct research into extracting complex information (entities and events) from the scientific literature to support metabolic model development.

Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing/Text Mining; working experience in biomedical text mining (event extraction); excellent knowledge in developing and adapting algorithms for text mining systems; strong publication record; excellent programming skills.

  • Duration of post: 1st January 2017 to 31st December 2018
  • Salary: £39,324 to £48,327 per annum

Research Environment

The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.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 will involve close collaboration with a team of experts focusing on metabolomics and cheminformatics. More information about the project: http://www.nactem.ac.uk/empathy/

Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).

Application form and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12531


Associate Research Scientist, UKP Lab, TU Darmstadt

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

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

to strengthen the group’s profile in the areas of Interactive Machine Learning (IML) or Computational Argumentation (CA). The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Interactive Machine Learning and Computational Argumentation are the rapidly developing focus areas in collaboration with partners in research and industry.

We ask for applications from candidates in Computer Science with a specialization in Machine Learning or Natural Language Processing, preferably with expertise in research and development projects, and strong communication skills in English and German. - The successful applicant in the area of interactive machine learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create the corresponding product prototypes. - The successful applicant in the area of Computational Argumentation will work on research activities in analyzing the discourse of future professionals while reasoning to automatically access their argumentation quality given small amounts of training data, and development activities for the research prototype. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP and/or ML) systems, experience in information retrieval, large-scale data processing and large-scale knowledge bases, and strong programming skills incl. Java. Experience with neural network architectures is a strong plus. Combining fundamental NLP research on Interactive Machine Learning or Computational Argumentation with practical applications in different domains will be highly encouraged.

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

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

Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the applications to: jobs@ukp.informatik.tu-darmstadt.de by 15.12.2016. The positions are open until filled. Later applications may be considered if the position is still open.

One Teaching Track and One Tenure Track position open at the Language Technologies Institute at Carnegie Mellon University (Pittsburgh, PA USA)

Employer: Language Technologies Institute, School of Computer Science, Carnegie Mellon University

Title: Assistant Teaching Professor and Assistant Professor

Specialty: Natural Language Processing, Computational Linguistics, Machine Learning and Statistical Methods for NLP, Social Media Analysis

The Language Technologies Institute (LTI) in the School of Computer Science (SCS) at Carnegie Mellon University invites applications for teaching-track and tenure-track positions, beginning Fall 2017. LTI is an academic department dedicated to the study of human language and information technologies, with approximately thirty faculty members. LTI is one of seven departments within SCS, which has over 200 tenure-track, research, and teaching faculty with expertise spanning traditional computer science, human computer interaction, language technologies, machine learning, computational biology, software engineering, and robotics. SCS offers a highly collaborative and uniquely interdisciplinary environment that promotes innovation and entrepreneurship in both teaching and research.


The teaching track is a career-oriented, renewable appointment with an initial appointment of three years. Initial teaching-track appointments are typically at the rank of Assistant Teaching Professor, with the possibility of promotion to the ranks of Associate Teaching Professor and Teaching Professor. These ranks are not tenured, but they do provide substantial opportunities for professional growth and long-term contributions to Language Technologies education at Carnegie Mellon University. Teaching track faculty contribute to the design of new curricula and the adoption of new teaching methods. For more information about this position, see: http://lti.cs.cmu.edu/teaching-track-faculty-position


We are also seeking to hire on the tenure track. Tenure track appointments are typically at the rank of Assistant Professor, with the possibility of promotion to the ranks of Associate Professor and Professor. Tenure-track applicants must have strong interests and accomplishments in both research and teaching. For more information about this position, see: http://lti.cs.cmu.edu/tenure-track-faculty-position

One Post-doctoral position in Statistical Machine Translation in CUNY (at Manhattan, NYC)

Employer: Department of Computer Science at Hunter College, University of New York Title: post-doctoral position Specialty: Machine Translation Location: Manhattan, NYC, NY

  • Deadline: Open until filled
  • Date posted: 6th November 2016
  • Contact: Dr. Jia Xu

The Statistical Machine Learning and Translation group of Dr. Xu at the City University of New York is inviting applications for one post-doctoral position. This is a splendid opportunity to conduct research blending very applied research (i.e. industrial-level Machine Translation systems) with foundational research in statistical machine learning. Dr. Xu’s group has an excellent record (e.g. winning first-place) in the international machine translation competitions during the last decade. The current research has evolved into exciting areas beyond statistical machine translation, such as in the foundations of machine learning and in frameworks in understanding the underlying geometry of languages.

Applicants should hold by the time the appointment begins a PhD (or its equivalent) in Computer Science, Computer Engineering, Statistics, Mathematics, Physics or in a related discipline. We are seeking for applicants committed to either (1) extending their current research program in statistical Natural Language Processing or (2) employing their analytical and engineering skills and join in our current research program. Therefore, this position can be also seen as an opportunity to fast-forward develop statistical NLP skills and conduct cutting-edge research in this field.

The position is for 1 year with the possibility of extending it up to 3 years. The starting date is flexible.

The Hunter College at the City University of New York may ask the post-doctor to take up a very moderate teaching load (can be waived based on research promise). The salary commensurate with qualifications and research potential and starts from $50K/year.

Hunter college is located in upper-east Manhattan. This is an extremely vibrant research location with numerous opportunities for collaboration. Hunter college is surrounded by top research labs (e.g. Google Research, Microsoft Research, Facebook, IBM Research), and many other university departments (e.g. Princeton, Columbia, NYU).

Applications should include a recent CV and optionally a research statement and 2 representative publications. Applications should be sent to Dr. Jia Xu by email to: jia.xu@hunter.cuny.edu including in the Subject title the keyword: “Application”.

All applicants will be notified upon receipt of the application by email.

This position will be advertised at http://jiaxu.org until is filled.

Hunter is committed to a policy of equal employment and equal access in its educational programs and activities. Diversity, inclusion, and an environment free from discrimination are central to the mission of the City University of New York.


Three fully funded PhD Positions in Statistical Natural Language Processing in CUNY (at Manhattan, NYC)

Employer: Department of Computer Science at Hunter College, University of New York Title: fully-funded PhD position Specialty: NLP

  • Location: Manhattan, NYC, NY
  • Deadline: Open until filled
  • Date posted: 6th November 2016
  • Contact: Dr. Jia Xu


The Statistical Machine Learning and Translation group of Dr. Xu at the City University of New York is inviting applications for fully-funded PhD student positions starting in 2017. This is a splendid opportunity to conduct research blending very applied research (i.e. industrial-level Machine Translation systems) with foundational research in statistical machine learning. Dr. Xu’s group has an excellent record (e.g. winning first-place) in the international machine translation competitions during the last decade. The current research has evolved into exciting areas beyond statistical machine translation, such as in the foundations of machine learning and in frameworks in understanding the underlying geometry of languages.

Applicants should hold by the time that begin their PhD studies a BSc, BEng (or its equivalent) in Computer Science, Linguistics, Computer Engineering, Statistics, Mathematics, Physics or related disciplines. We are seeking for very motivated students with enthusiasm and dedication in conducting cutting-edge research in statistical methods over massive amounts of data. Natural Language Processing is the prototypical domain where Machine Learning and Big Data are required to come together.

The typical duration of the PhD program is from 3 to 4 years.

The Hunter College at the City University of New York asks that the PhD candidate should take up two teaching assistantships per year. The admitted student will be offered to have the tuition fees covered and also stipend sufficient to cover the living cost.

Hunter college is located in upper-east Manhattan. This is an extremely vibrant research location with numerous opportunities for internships and collaboration. Hunter college is surrounded by top research labs, such as Google Research, Microsoft Research, Facebook, and IBM Research.

Application material: CV and optionally a statement of purpose letter, GRE, and TOELF/IELTS results. Applications should be sent to Dr. Jia Xu by email to: Jia.Xu@hunter.cuny.edu including in the Subject title the keyword: “PhD".

All applicants will be notified upon receipt of the application by email.

This position will be advertised at http://jiaxu.org until the position is filled.

Hunter is committed to a policy of equal employment and equal access in its educational programs and activities. Diversity, inclusion, and an environment free from discrimination are central to the mission of the City University of New York.


Funded PhD Position in Natural Language Processing in Barcelona

  • Employer: Department of Information and Communication Technologies at Universitat Pompeu Fabra
  • Title: PhD studentship position
  • Specialty: NLP
  • Location: Barcelona, Spain
  • Deadline: August 8th, 2016 (or until filled)
  • Date posted: 29th July 2016
  • Contact: Prof. Horacio Saggion


The Department of Information and Communication Technologies at Universitat Pompeu Fabra in Barcelona, Spain, invites applications for a PhD studentship position that is associated with the María de Maeztu Units of Excellence Research Program of the Spanish Government (http://www.upf.edu/mdm-dtic), and involves joint work of the research labs of profs. Horacio Saggion and Ricardo Baeza-Yates. This position will be funded under the FPI call to be launched by the Spanish Ministry of Economy and Competitiveness.

Project Description

In the context of our Maria de Maeztu (MdM) project "Mining the Knowledge of Scientific Publications" ( see http://www.upf.edu/mdm-dtic) the PhD student will carry out a research project on the more focused area of automatic research paper assessment which concerns a number of interesting research questions including but not limited to:

  • automatic research paper evaluation
  • automatic research paper/author impact prediction
  • automatic novelty evaluation

The PhD will benefit from the resources developed during MdM project: availability of large scale open scientific repositories, natural language processing technology adapted to scientific text processing, document retrieval technology, etc. as well as the expertise of the MdM team members.

Applicants

Candidates should hold a M.Sc. in Computer Science or related field with a solid background in Natural Language Processing and be proficient in spoken and written English. Experience with recent advances in Machine Learning and Information Retrieval would be highly valuable. Knowledge of statistical analysis is highly desirable.

More information

For informal inquiries, prospective candidates may contact professor Horacio Saggion at horacio DOT saggion AT upf DOT edu

For more information please check the official announcement at

https://portal.upf.edu/web/etic/automatic-research-assessment?p_p_id=56_INSTANCE_MaAxd6TFfhia&p_p_lifecycle=0&p_p_state=normal&p_p_mode=view&p_p_col_id=column-1&p_p_col_count=1

Research Fellow in Biomedical Text Mining, University of Manchester, UK

  • Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
  • Title: Research Fellow
  • Speciality: Natural Language Processing, Text Mining
  • Location: Manchester, UK
  • Deadline: August 13, 2016
  • Date posted: July 18, 2016
  • Contact: sophia.ananiadou@manchester.ac.uk

Applications are invited for a postdoctoral research fellow in Biomedical Text Mining at the National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester.

The objective of this BBSRC funded post in collaboration with Unilever is to conduct research into extracting complex information from the scientific literature to support metabolic pathway curation using text mining methods.

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 Text Mining; strong track record of high-quality papers in conferences such as ACL, EMNLP, etc., and in high quality journals; excellent programming skills; proven ability to develop independently research proposals.

  • Duration of post: until 31st March 2018 with possibility of extension
  • Salary: £38,896 to £47,801 per annum

Research Environment

The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.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 will involve close collaboration with a team of experts focusing on metabolomics and cheminformatics. More information about the project: http://www.nactem.ac.uk/empathy/

Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).

Application form and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=11856

Computational Linguist-Morphology

  • Employer: Esprit de Corps Corporation (EdC), US
  • Title: Computational Linguist-Morphology
  • Specialty: Application of Finite State Transducers (FST) to language processing technologies, development of FST networks for languages, integration of morphological analyzers.
  • Location: Various US Locations
  • Deadline: Open
  • Date posted: June 19, 2016
  • Contact: Jim Lay


EdC provides linguistic and cultural insight in support of US national interests. We are a woman owned, small business, and an equal opportunity employer.

The Computational Linguist-Morphology provides unique expertise with the application of FST to language processing technologies, to include the development of FST networks for languages, the integration of morphological analyzers in multilingual databases/search engines and the development of APIs for managing FST I/O in a multilingual environment.

Qualifications

  • A master's degree in computer science and/or linguistics, or in a related field; eight (8) years related experience in FST technologies for language applications may be substituted for a master's degree.
  • Within the last ten (10) years, shall have a minimum of seven (7) years experience programming language networks in one or more FST applications such as XSFT, Stuttgart Finite State Transducer Toolkit, OpenFST, FOMA, or other product with equivalent functional capabilities.
  • Shall have a minimum of five (5) years experience coding with two (2) or more of the following: C, C++, or Java. Shall also have a minimum of five (5) years experience with Perl and/or Python scripting languages.
  • Within the last ten (10) years, shall have a minimum of five (5) years experience with linguistics and language structure, language processing technologies, and/or with applying morphologies to multilingual databases/search engines.
  • Shall have a minimum of five (5) years experience with two (2) or more foreign languages. Shall have demonstrated experience with international encodings, to include converting and handling multilingual encoding, such as UTF-8.

Applicants must be United States citizens able to acquire a personal security clearance.

For more information about the post and for applications: http://edcknowledge.com/join-the-corps-2/, Search and apply for the position titled "Computational Linguist-Morphology".

Computational Linguist

  • Employer: Esprit de Corps Corporation (EdC), US
  • Title: Computational Linguist
  • Specialty: Integration of NLP Modules, Experimentation with User Interfaces for Analytic Support, Web Services for Querying Extracted Results.
  • Location: Various US Locations
  • Deadline: Open
  • Date posted: June 19, 2016
  • Contact: Jim Lay


EdC provides linguistic and cultural insight in support of US national interests. We are a woman owned, small business, and an equal opportunity employer.

The Computational Linguist provides unique expertise with the application of computer science to language processing technologies, to include experimentation with, and integration of, unique NLP modules, experimentation with user interfaces for analytic support, web development, and development of web services for querying extracted results.

Qualifications

  • MA in computer science and/or linguistics, or in a related field (8 years related experience may be substituted for a Master's Degree).
  • Within the last 10 years shall have a minimum of 7 years experience each programming: C, C++, or Java.
  • Within the last 5 years, shall have a minimum of 3 years programming with two or more scripting languages (e.g. Perl, Python).
  • Within the last 10 years, shall have a minimum of 5 years experience with linguistics and language structure, language processing technologies, and/or with applying ontologies to NLP applications.
  • A minimum of 5 years experience with two or more foreign languages is required.
  • Shall have demonstrated experience developing software in a Linux environment, with Semantic Web technologies (e.g. RDF, OWL), and with international encodings, to include converting and handling multilingual encoding, such as UTF - 8 is required.

Applicants must be United States citizens able to acquire a personal security clearance.

For more information about the post and for applications: http://edcknowledge.com/join-the-corps-2/, Search and apply for the position titled "Computational Linguist".

Research Associate/Fellow in Machine Learning, University of Sheffield, UK


We have an opening for a 3-year position of Research Associate or Research Fellow in Machine Learning with applications to Machine Translation and Multimodal Language Processing. This position is funded by the ERC MultiMT project: Multi-modal Context Modelling for Machine Translation, led by Prof. Lucia Specia (www.dcs.shef.ac.uk/~lucia) at the University of Sheffield.

This is a highly interdisciplinary project involving Natural Language Processing, Computer Vision and Machine Learning. Its goal is to devise methods and algorithms to exploit global multi-modal information for context modelling in Machine Translation. The post holder will be expected to investigate new ways to acquire multilingual multi-modal representations, and new machine learning and inference algorithms that can learn from these rich context models to generate high quality translations. In addition, if appointed as Research Fellow, the post holder will be expected to make significant contributions to multi-modal language processing in general, drawing from their experience in Computer Vision and Natural Language Processing.

This is an opportunity to work in a well-connected international team with world-leading reputation in the Natural Language Processing (NLP) research group at the University of Sheffield. The NLP group is well known internationally for its research, and is one of the largest research groups in the area in Europe.

This post offers excellent opportunities for publications, project visits and conference trips. Applicants should have (for Research Associate (RA) and Research Fellow (RF) posts):

  • PhD (or equivalent work experience) in Computer Science, Statistics, Mathematics or related areas
  • Significant experience and track record in Machine Learning (RA and RF)
  • Strong publication record commensurate with career stage (RA and RF)
  • Experience and strong track record in Computer Vision (desirable for RA, required for RF)
  • Experience and strong track record in Natural Language Processing (desirable for both RA and RF)
  • Strong programming experience, particularly in Python or C++. (RA and RF)

This post is fixed-term with a start date from August 2016 (or soon after) and duration of 3 years with possibility of extension to 5 years.

Salary range: £28,847 to £46,414 per annum.

For informal inquiries contact Dr. Lucia Specia: L.Specia@sheffield.ac.uk

For more information about the post and for applications: http://www.shef.ac.uk/jobs, Search and apply for jobs using reference number UOS014018


Doctoral Researcher at UKP/KRITIS, TU Darmstadt

KRITIS ("Kritische Infrastrukturen: Konstruktion, Funktionskrisen und Schutz in Städten"), a new interdisciplinary research training group at Technsiche Universität Darmstadt and funded through the German Research Foundation, is currently seeking a Doctoral Researcher to start on 1 October 2016.

KRITIS researches systems for technical supply and disposal, and for communication and transport, which have become the central nervous system of modern cities. Their disruption can trigger dramatic crises. Modern city infrastructures are increasingly vulnerable not only to external threats (natural disasters, terrorist attacks, and cyber attacks) but also due to their inherent complexity and interdependence. Our aim is to understand and describe these complex systems in their spatial and temporal contexts. This is done in three main research areas:

  1. We want to ensure that technical infrastructures are constructed with the term "critical" in mind. We therefore ask what technical-functional needs, and political and social considerations, are relevant, and how these vary according to the systems' historical and spacial context.
  2. We assume that the complex spatial and temporal arrangements become particularly visible during infrastructural-functional crises. We therefore investigate failures of urban infrastructures, including the conditions contributing to their vulnerability or resilience.
  3. Finally, we ask how we can best organize protection against or preparation for infrastructural-functional crises (so-called "prevention and preparedness").

Research in the training group takes an interdisciplinary approach, with cooperation among the following specialities: space and infrastructure planning, modern and contemporary history, medieval history, philosophy of technology, comparative analysis of political systems, ubiquitous knowledge processing, urban design and planning, rail systems, and computer science for architecture and construction.

In this area, the discipline of ubiquitous knowledge processing (Prof. Iryna Gurevych) is concerned with the interactions between urban infrastructure (e.g., transport, telecommunications), communication in social media, and the relevant spatial and temporal analysis methods from the perspective of adaptive information and text processing. This will be of particular interest to doctoral candidates in the fields of real-time text analysis which can be applied to the early detection of crises, to public opinion-making, or to crisis management through automated evaluation of (online) content such as Twitter.

Possible dissertation topics include:

  • Social-spatial differences of criticality: location- and class-specific text-analytic mining of argumentation on urban infrastructure in social media
  • Mining of arguments on urban infrastructure in social media for cascading reactions (i.e., spatio-temporal spread of social media responses to the collapse of urban infrastructure)
  • Early recognition of vulnerability: Real-time monitoring of information on hazards to urban infrastructure in social media
  • User expectations on the speed of resolution of infrastructural failures – comparison and analysis of tweets across national boundaries

For discussion or advice on further possible research topics and organizational issues, please contact Prof. Iryna Gurevych at jobs@ukp.informatik.tu-darmstadt.de.

Requirements: The successful applicants should produce a doctoral dissertation related to one or more of the above-noted research priorities. This dissertation should be completed within three years and submitted to one of the departments of Technische Universität Darmstadt. Further information on KRITIS's scientific program and its participating professors will be available soon on the following website: http://www.kritis.tu-darmstadt.de

It is expected that all members of the research training group will be intensively engaged in interdisciplinary cooperation leading to scholarly publications and lectures. To this end, regular participation in seminars, symposia, workshops, etc. is required, which necessitates the doctoral candidates being domiciled in the Rhine-Main area.

Working environment and conditions: KRITIS offers an excellent research infrastructure for doctoral students who wish to carry out their own research project within an innovative and internationally networked program. The members of the group work in shared offices under the support and patronage of participating professors. Among the special services include the possibility of a financed stay abroad in one of four internationally renowned partner universities. We also work with various partners in the private and public sector (companies, government offices, and other organizations) at which candidates can complete internships.

Salaries for doctoral candidates depend on qualifications and experience, and will be in line with the collective agreement for employees at TU Darmstadt (TV-TU Darmstadt). The positions are limited to three years and include, depending on the field, 65% to 100% (full-time) employment.

Your application: TU Darmstadt strives to increase its number of female employees, and as such particularly encourages women to apply. All other things being equal, applicants who have a degree of disability of at least 50% (or the equivalent) will receive preference. Please prepare your application in English or German, and compressed as a single file (up to 6 MB). Applications should be sent by e-mail to Prof. Gurevych at jobs@ukp.informatik.tu-darmstadt.de by 10 July 2016. The application should include a CV listing language skills and overseas experience, scanned copies of academic credentials, and a sketch of up to five pages for a doctoral project.

We look forward to receiving your application!

Doctoral Researcher in NLP at TU Darmstadt and/or University of Heidelberg

The Research Training Group „Adaptive Information Preparation from Heterogeneous Sources“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling a position for three years, starting as soon as possible: Doctoral Researcher in Natural Language Processing

The position provides the opportunity to obtain a doctoral degree with an emphasis on the guiding theme D1: Multi-level models of information quality, under the leadership of Prof. Dr. Iryna Gurevych (UKP Lab, TU Darmstadt). A possible research focus of the position is an automatic claim checking with its applications in the domain of computational journalism. However, other suitable topics may be proposed as well. The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale.

The goal of AIPHES is to conduct innovative research in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment are being developed. AIPHES investigates a novel scenario for information preparation from heterogeneous sources, within the application context of multi-document summarization. There exists close interaction with end users who prepare textual documents in an online editorial office and therefore profit from the results of AIPHES.

Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler, Dr. Meyer), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann). 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 emphasizes close contact between students and their advisors, has 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 actively supports its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.

Prerequisites

We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be 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.

Applications should include:

  • a motivational letter explaining the applicant’s possible contribution to the guiding theme D1,
  • 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 June 30th, 2016 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address jobs@ukp.informatik.tu-darmstadt.de.

Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt

The Department of Computer Science at Technische Universität Darmstadt invites applications for the position of Full Professor (W3) for Real-Time Data Analytics to be appointed as soon as possible.

We are seeking an outstanding researcher to establish the Department’s new area of real-time data analytics through research and teaching. The main focus of the professorship will be on excellent, method-oriented research, with close links to systems and applications. It is also expected that the successful candidate plays a formative role in cross-department and interdisciplinary research activities; the bridge to engineering departments of the university, in particular to the department of mechanical engineering, is particularly important in this respect.

Relevant topics include real-time data analytics on dynamic data streams of various types (including sensor data, text, and images), adaptive information processing and integration, and interactive machine learning. Further topics of research include data analysis and its applications in the mining of data and data streams of heterogeneous nature, quality, and quantity and in the support of decision-making processes, decision management, and the creation of self-organizing systems. Example application areas include automotive engineering, transport and logistics, and cognitive information processing for information validation on the Web.

We expect applicants to have interdisciplinary experience in the use of data analysis methods in cooperation with scientists from other fields as well as with industrial partners. The professorship is intended to strengthen those profile areas of TU Darmstadt in which real-time requirements and interactivity play a central role, such as the Internet and digitization and their associated research fields such as data science, Industry 4.0, autonomous driving, smart transport and energy networks, smart buildings, but also natural language processing, cognitive science, and cybersecurity.

In addition to an outstanding academic CV, applicants must demonstrate a strong commitment to teaching computer science (incl. foundational courses) at the Bachelor’s and Master’s levels. A willingness to participate in academic self-administration is also expected.

Technische Universität Darmstadt is an autonomous university with a wide-ranging excellence in research, an interdisciplinary profile, and a strong focus on engineering as well as on information and communication technologies. Our Department is one of the leading national Computer Science departments and regularly ranked in the top group in national rankings.

Employment will be on a non-tariff basis, with qualification-based compensation based on the German W-level salary. Applicants who are already professors classed as German civil servants (Beamter) can retain this status. Employment regulations from §§61 and 62 of the Hessisches Hochschulgesetz apply.

Technische Universität Darmstadt is committed to increase the proportion of female scientific staff and therefore particularly encourages women to apply. All other things being equal, we will give preference to candidates with a degree of disability of at least 50 (or the equivalent).

Applications, including all the usual supporting documents, should be submitted to the Dean of the Department of Computer Science, Technische Universität Darmstadt, Hochschulstr. 10, 64289 Darmstadt, Germany, e-mail dekanat@informatik.tu-darmstadt.de. Please quote reference No. 244.

For further information, please contact Prof. Dr. Iryna Gurevych, tel. [+49] (0)6151 16 25290, gurevych@ukp.informatik.tu-darmstadt.de

NLP Postdoctoral Researcher at UNSW, Australia

  • Employer: The University of New South Wales, Australia
  • Title: Research Associate/Fellow
  • Specialty: NLP, Knowledge Graph
  • Location: Sydney, Australia
  • Deadline: June 6th, 2016
  • Date posted: May 14th, 2016
  • Contact: Wei Wang (weiw@cse.unsw.edu.au)

POSITION DESCRIPTION

A postdoctoral position is available in School of Computer Science and Engineering at the University of New South Wales, Australia. The successful candidate will work with Dr. Wei Wang on utilizing Natural language processing (NLP), data mining, and semantic web to develop novel algorithms, tools and methods for constructing and maintaining domain-specific knowledge graphs from vast amount of unstructured/semi-structured data sources. This position is funded by Data to Decisions Cooperative Research Centre (D2D CRC), which was established in 2014 with a grant of A$25 million from the Australian Government, researchers and industry to provide the Big Data capability resulting in a safer and more secure nation and a sustainable Big Data workforce for Australia.


POSITION REQUIREMENTS

Essential criteria:

  • Proven ability to undertake research in a relevant research area (e.g. natural language processing, data mining, knowledge graph) 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, KDD, IJCAI, AAAI, ICML, NIPS, SIGMOD, VLDB) and journals.
  • 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. Candidates with pending degrees who will successfully defend their dissertations by August 1, 2016 will also be considered.


Desirable criteria:

  • Knowledge of statistical natural language processing.
  • Knowledge of knowledge graph construction and applications.
  • Experience with analysing large text corpora using a high-performance computing environment.
  • Experience with python/R


SALARY RANGE AND CONTRACT LENGTH

  • Research Associate: A$86,438 - A$92,453 per year (plus employer superannuation)
  • Research Fellow: A$97,090 - A$114,454 per year (plus employer superannuation)

This is a fixed term position of one year with further renewal up to January 2019, subject to funding.


ENVIRONMENT

The School of Computer Science and Engineering in UNSW, located in Sydney, is one of the largest and leading computing schools in Australia. It offers both undergraduate and postgraduate programs in Software Engineering, Computer Engineering, Computer Science and Bioinformatics, as well as a number of combined degrees with other disciplines. It attracts excellent students who have an outstanding record in international competitions (such as Robocup).


APPLICATION

Please send a statement of interest, an academic CV (in pdf format) to Wei Wang (weiw@cse.unsw.edu.au) with the subject line starting with "[CRCPostdoc]". For informal queries, please send an email to weiw@cse.unsw.edu.au.




Computer Science Postdoctoral Researcher in Natural Language Processing for Social Science

  • Employer: University of Pennsylvania
  • Title: Postdoctoral Researcher
  • Specialty: NLP
  • Location: Philadelphia, PA
  • Deadline: May 15th, 2016
  • Date posted: April 26th, 2016
  • Contact: Professor Lyle Ungar: ungar@cis.upenn.edu

Summary

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 primary responsibility will, of course, be producing top-quality published research in areas of interest to you and the WWBP team. You will be expected to lead multiple peer-reviewed publications each year and to support (as secondary author and technical expert) many more publications. As part of that latter process, we would like you to serve as the equivalent of a “Chief Technology Officer” of the WWBP, providing technical oversight and mentoring to the programmers and data scientists who build and maintain our software and hardware infrastructure, and who do the vast bulk of the data collection and analysis for the WWBP.

The ideal candidate will have research experience in computational linguistics and applied machine learning. They 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 wwp.org for example publications.


Approximate Start Date: Summer 2016


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.



Research Scientist, Natural Language Processing

  • Employer: EMR.AI Inc.
  • Title: Research Scientist
  • Specialty: NLP
  • Location: San Francisco, CA
  • Deadline: May 20th, 2016
  • Date posted: April 21th, 2016
  • Contact: David Suendermann-Oeft (david@emr.ai)

Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.

Summary

EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others.

This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.

Responsibilities

  • Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.
  • Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.
  • Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.
  • Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.
  • Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.

Skills

PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.

Benefits

EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.

How to Apply

Please send your application documents to jobs@emr.ai

Contact

EMR.AI Inc.

90 New Montgomery St

San Francisco, CA 94105, USA

phone: +1-415-200-8535

e-mail: info@emr.ai

www: http://emr.ai


Research Scientist on Natural Language Processing

  • Employer: IBM Research Ireland
  • Title: Research Scientist
  • Specialty: NLP, Machine Learning
  • Location: Dublin
  • Deadline: May 5th, 2016
  • Date posted: April 11th, 2016
  • Contact: link to application page


Ireland is accepting applications for full-time researchers in the area of natural language processing. The ideal candidate will have a PhD degree in computational linguistics or in computer science with a specialisation in Natural Language Processing (NLP). Prior experience in the area of text analytics with information extraction, information retrieval and machine learning are highly desirable, and experience with corpus linguistics or natural language understanding are a plus. Strong programming skills in Java are required.

The successful research candidate must have demonstrated ability to define research plans, carry out leading research, and publish research results through professional journals, academic conferences, and patents. As a researcher you will be expected to organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions have a significant impact.


Postdoc Researcher on Vision and Language

  • Employer: University of Liverpool
  • Title: Postdoc
  • Specialty: Computer Vision with an interest in human vision/language behaviour
  • Location: Liverpool UK
  • Deadline: April 20th, 2016
  • Date posted: March 28, 2016
  • Contact: link to application page

Applications are invited for a Postdoctoral Research associate position to study the relationship between visual/spatial representations and language. Language is often used to describe the visual world and this is done by labelling objects in the world with various categories such as roles (e.g., agent, goal). There is now a large infant social cognition literature which shows how categories like agents and goals may be identified using simple visual heuristics. In this post, we will strengthen these links by experimentally manipulating visual cues to see how they influence language choices in adults and children. In addition to the experimental study of these links, we will also develop computational models that use computer vision techniques to track the interaction of objects in videos and link these visual codes to the descriptions of the actions. We are most interested in people with a computational background who have an interest in human vision/language processing.

This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the ESRC International Centre for Language and Communicative Development (LUCID, http://www.lucid.ac.uk/), a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster. You should have (or be about to obtain) a PhD in the field related to Computer Science, Psychology, Cognitive Science, or related disciple. The post is available for 3 years.


Postdoc Positions at Johns Hopkins University

  • Employer: Johns Hopkins University
  • Title: Postdoc
  • Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine
  • Location: Baltimore, MD
  • Deadline: March 31, 2016
  • Date posted: March 1, 2016
  • Contact: http://www.clsp.jhu.edu/employment-opportunities/

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

The center has a number of postdoctoral positions available for the coming year. Possible research topics include:

  • Trend Detection in Social Media
  • Broadly Multilingual Learning of Morphology
  • Stochastic approximation algorithms for subspace and multi-view representation learning
  • Analysis of large-scale time series data in healthcare

Host faculty include: Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria


Associate/Full Professor in Computational Linguistics at Stony Brook University

Job Description

The Department of Linguistics at Stony Brook University invites applications for a tenured appointment in computational linguistics, beginning Fall 2016 or Fall 2017. This is a senior appointment at the Associate or Full Professor level.

The successful candidate will have a PhD (preferably in Linguistics or Computer Science), an outstanding research profile in Computational Linguistics (ideally in areas that complement existing departmental strengths), a strong track record in grant acquisition, and teaching and advising experience at the graduate and/or undergraduate levels.

They will also be expected to

  • Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,
  • Initiate new collaborations and expand existing ones with other computational research groups on campus, in particular in the Department of Computer Science and the Institute for Advanced Computational Science,
  • Strengthen the department's connections with the local IT industry.

Salary will be commensurate with education and experience.

Application

Applications must be submitted via AcademicJobsOnline: https://academicjobsonline.org/ajo/jobs/6983


Research Scientist at the Allen Institute for Artificial Intelligence

  • Employer: Allen Institute for Artificial Intelligence (AI2)
  • Title: 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 2016
  • Date posted: 02/09/2016
  • Contact information: ai2-info@allenai.org
  • Website: http://allenai.org/jobs.html

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 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
  • Natural language processing
  • Diagram understanding
  • Visual knowledge extraction and visual reasoning

And more….

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 AI2’s 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, computer vision and machine learning, or question answering and explanation. We look favorably upon extensive work experience and publishing demonstrating application of your research.

Why AI2

In addition to AI2’s core mission of being a leader in the field of AI research, we also aim to create a superb team environment and to invest in each team member’s personal development. Some highlights are:

  • We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning right alongside us;
  • We value diversity of thought – we seek Research Scientists who can bring novel experiences and modes of problem solving to our leading-edge mission. If you are creative and efficient in your approach and insightful in your questioning, AI2 could be a great environment for you;
  • We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave;
  • We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures;
  • We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, we have the defending Super Bowl champions, and we have so much else. We even have kayaks for you to paddle right outside our front door;
  • We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!

Application Process

Visit our website for more information: http://allenai.org/jobs.html


Software Engineer - Machine Learning / NLP (Chinese) at SYSTRAN

  • Employer: SYSTRAN
  • Title: Software Engineer
  • Topics: Machine Learning, Natural Language Processing, Machine Translation
  • Location: San Diego
  • Deadline: Open until filled
  • Date Posted: January 29, 2016
  • Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na

SYSTRAN is currently seeking an experienced Software Engineer specializing in Machine Learning / NLP to join our R&D team in San Diego to develop machine translation systems.

The ideal candidate must have a combination of research and implementation skills, including significant programming experience. Hands-on experience with machine learning, including deep neural network, text classification, statistical techniques for NLP or a related field, is highly desirable.

Responsibilities include software development, experimentation, analysis of results, and building systems that combine linguistics and statistical language models for machine translation centering on Chinese language.

Key Qualifications

  • Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology
  • Good algorithmic knowledge of machine learning
  • Experience writing and debugging software
  • Strong communications skills
  • Ability to work well as part of a team
  • Fluent in English.
  • Fluent in Chinese is a plus

Education and Experience

  • MS or Ph D in Computational Linguistics / Computer Science or relevant field.
  • 2+ years work experience preferred

Benefits

  • Successful candidates will be offered a competitive salary based on their qualifications and experience.


Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee

  • Employer: University of Dundee
  • Title: Lecturer/Senior Lecturer/Reader
  • Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence
  • Location: Dundee, UK
  • Deadline: 27 February 2016
  • Date Posted: 12 January 2016
  • Contact: Prof. Chris Reed (see http://arg.tech/lecturer)

£34,576 to £55,389 Full Time, Permanent

The University of Dundee’s School of Science & Engineering is advertising several permanent posts including one covering the Centre for Argument Technology. We are particularly keen to receive applications from candidates in Computational Linguistics to expand the group’s research in Argument Mining (see http://argmining2016.arg.tech and http://arg.tech/am), but welcome applications in all areas of the overlap between argumentation and artificial intelligence. A strong publication profile is essential, and for more senior appointments, so is a track record of funding success.

For further information about the Centre for Argument Technology, please see http://arg.tech or contact Prof. Chris Reed; for more information about the position, see http://arg.tech/lecturer. General details follow.

Summary of Job Purpose and Principal Duties

The University of Dundee is seeking an exceptional candidate to join one of our Computing research groups, based within the School of Science and Engineering. The successful candidate will develop new research lines within either the (i) Human Centred Computing Group; (ii) the Centre for Argument Technology; or (iii) the Space Technology Centre. Full information on the current research in each group can be found in the Further Particulars.

The successful candidate is expected to have a strong track record of research and a clear research plan that articulates with (or expands significantly) one of these areas. They will be expected to contribute to the development of research in this area by publishing in the highest quality journals and attracting appropriate research funding. For appointments at Grade 8 and 9, candidates are expected to show evidence of having attracted independent funding. The School encourages applications from holders of personal Fellowships.

Additionally, the successful candidate will be expected to take an active role in the teaching of undergraduate computing programmes as well as supporting teaching at Masters level.

Job Summary

The appointee will be expected to contribute to research in Computing and to teaching and administration within the School of Science and Engineering. They will be expected to:

  • Contribute to the ongoing research in one of the three research groups described above.
  • Contribute to the generation of external research funding.
  • Publish in high quality research journals and major international conferences.
  • Teach at undergraduate and post-graduate level.
  • Supervise students at all levels (honours and MSc projects, PhD).
  • Undertake administrative duties.

Application Requirements

In addition to the online form, applicants must include with their application:

  • Cover letter outlining fit to role.
  • Research plan (1-2 pages) covering proposed research over the first three years of the appointment.
  • Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.


Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory

  • Employer: US Naval Research Laboratory
  • Title: Postdoctoral Research Fellow
  • Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence
  • Location: Washington, DC
  • Deadline: Open until filled
  • Date Posted: January 20, 2016
  • Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)

Research focus: The Postdoctoral Fellow will collaborate on various projects in reasoning, including (but not limited to) building a unified computational framework of reasoning; investigating how people engage in explanatory reasoning; and testing a system that reasons about time and temporal relations.

Supervisor: Sunny Khemlani, PhD

Key qualifications: A Ph.D. in cognitive psychology, cognitive science, or computer science, with experience in higher level cognition, experimental design and data analysis, or cognitive modeling. Experience with theories of reasoning, computer programming, and cognitive modeling is a strong plus.

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

Program and compensation: The Fellowship operates through the NRC Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). Only US citizenship or green card holders are eligible for the program. Fellows are compensated through a research stipend of ~$75,000/year.

To apply: Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.


Internship positions available at Juji, Inc.

  • Employer: Juji, Inc.
  • Title: Intern
  • Location: Saratoga, CA
  • Deadline: open until all the positions are filled
  • Date Posted: January 14, 2016

Description: Have you ever watched the movie Her? Have you ever wondered or wished to have a virtual partner just like Samantha, who could tell you what you really are, whom your best partner may be, and even cheers you up? At Juji, we are building a hyper-personalized, virtual REP (Responsible, Empathetic Pal) for everyone. Your REP not only understands who you are, including your personality, motivations, and strengths, but it can also chat with you to learn and help fulfill your certain needs.

We are seeking highly motivated and talented students, who are eager to help us tackle great technical challenges at Juji and to expand their knowledge and skills in the real world. We are especially interested in students who have had worked or love to work in the following areas: Artificial Intelligence, Natural Language Processing/Natural Language Generation, Machine Learning, Human-Computer Interaction, Information Visualization/Visual Analytics, and Cognitive Science.

We have multiple positions on two main tracks:

  • Software development. If you love to create amazing software technologies and systems for real users, this is the track for you. You are expected to own and deliver a relatively independent project that will contribute to our cutting-edge product development effort.
  • Scientific research. If you love to design and conduct scientific experiments to answer a specific set of research questions, this is the track for you. You will work on a government funded research project on understanding human trust in a digital environment. You are expected to play a critical role in designing and conducting novel research studies and writing papers that lead to scientific publications.

Qualifications Outstanding current students towards a bachelor or higher degree in the area of Computer Science, Computer Engineering, or equivalent disciplines are encouraged to apply. Strong software development or visual design skills are a plus.

To apply: Please email a copy of your resume to the following address: jobs@juji-inc.com with a subject line “Summer Internship 2016”, and state your track preference in your email body.


Postdoctoral Fellow in Natural Language Processing / AI 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, Artificial Intelligence, Predictive Modeling
  • Location: Boston, MA
  • Deadline: Open until filled
  • Date Posted: January 8, 2016
  • 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 high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.

Supervisor: Alexander Turchin, MD, MS, FACMI

Required skills: experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with artificial intelligence technologies, predictive modeling, Big Data and medical terminologies / ontologies is a strong plus.

Education: PhD in computer science, biomedical informatics, linguistics, or a 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: Immediately.

Compensation: according to NIH (NRSA) stipend levels.

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

Retrieved from "https://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&oldid=11814"