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Employment opportunities, postdoctoral positions, summer jobs

2019-07-17T23:05:25Z

Sbowman: Add NYU position.

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== Full-Time Research Engineer, New York University ==

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

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

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

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

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

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

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

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

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

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

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

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

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

* Employer: [https://www.univ-rennes1.fr/ University of Rennes 1]
* Title: Postdoctoral Researcher
* Specialty: Natural language processing
* Duration: 24 months
* Location: Lannion, France
* Deadline: until filled
* Date posted: April 23, 2019
* Contact: Gwénolé Lecorvé (gwenole.lecorve@irisa.fr), Jonathan Chevelu (jonathan.chevelu@irisa.fr)

'''Overview'''

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

The Expression team [https://www-expression.irisa.fr/] works on natural language processing (NLP), be it through texts, speech or gestures. In particular, it focuses on the expressive components of the human languages.

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

The recruited person will work on a paraphase generation and propose solution to integrate register-specific stylistic constraints. She/he is expected to investigate on the use of statistical and neural paraphrasing systems, that is:
* Training of a baseline systems using either statistical or neural approaches.
* Intregration of constraints formulated as sequential patterns.
* Organization of evaluation campaigns.

'''Job requirements'''

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

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

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

'''Overview'''

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

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

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

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

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

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

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

* Employer: [https://www.informatik.tu-darmstadt.de/ukp/ukp_home/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: Natural Language Generation, Semantics and Discourse Processing, Multi-document Information Consolidation
* Location: Darmstadt
* Deadline: April 30, 2019 (or until filled)
* Date posted: April 12, 2019
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment

The [https://www.informatik.tu-darmstadt.de/ukp/ukp_home/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

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

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

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

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

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

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

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

== Senior Research Scientist - Natural Language Processing at Bosch Research ==

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

'''Company Description'''

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

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

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

'''Job Description'''

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

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

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

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

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

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

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

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

ESSENTIAL SKILLS

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

LOCATION - Bott and Co, Wilmslow, Cheshire

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

DURATION - 30 months - starting ASAP

CLOSING DATE - 07/04/2019

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

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

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

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

'''Responsibilities'''

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

'''Profile'''

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

'''Offer'''

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

'''Interested'''

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

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

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

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

'''Requirements'''

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

'''Evaluation'''

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

'''Application'''

Applications must be submitted electronically at the attached www address - the electronic application form (only reference letters, if not given directly to the applicant, may be sent by email). The applicants should provide the following documents with their application:
*An academic CV, a list of publications, and a motivation letter.
*A scanned copy of the PhD diploma, or a letter certifying submission of doctoral thesis for the defense.
*One external reference letter, and one support letter (expression of interest) from a member of the academic staff of the Faculty of Informatics of Masaryk University. These letters, if cannot be attached by the applicant him/herself, may be sent to the e-mail address hales@fi.muni.cz.

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

'''Contact'''

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

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

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

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

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

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

For full consideration, candidates should submit the following materials electronically '''''as a single PDF file''''' to Dr. Yu-Ru Lin at <yuruliny@gmail.com>:
# A brief statement of interest describing your relevant background
# Current CV
# The names and contact information for two references (letters of recommendation will be solicited from finalists)
# Two publications or other writing samples
Please include "PostDoc Application 2019" in the email subject line.

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

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

== Assistant Professor Position at The University of Memphis ==

* Employer: University of Memphis
* Rank or Title: Assistant Professor
* Specialty: ML/NLP with particular interest in educational technologies
* Location: Memphis, Tennessee
* Deadline: 1/7/19 but applications accepted until search completed
* Date Posted: 11/28/18
* Contact email: cconnor2@memphis.edu
* Application link: [https://workforum.memphis.edu/postings/20504]

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

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

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

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

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

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

To apply, please visit [https://workforum.memphis.edu/postings/20504]. Include a cover letter (please include a reference to this position as “CS-IIS”), curriculum vitae, statement of teaching philosophy, research statement, and three letters of recommendation. Direct all inquiries to Corinne O’Connor (cconnor2@memphis.edu).

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

== Research Associate in Text Mining, University of Manchester, UK ==

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

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

Post Objectives:

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

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

3. To develop a classification system for risk assessment.

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

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

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

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

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

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

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

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

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

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

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

== Associate Research Scientist, UKP Lab, TU Darmstadt ==

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: Interactive Text Analysis and Natural Language Processing Tools
* Location: Darmstadt
* Deadline: December 15, 2018 (or until filled)
* Date posted: November 22, 2018
* Contact: https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/

The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

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

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

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

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

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

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

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

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

== Associate Research Scientist, UKP Lab, TU Darmstadt ==

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: Natural language processing
* Location: Darmstadt
* Deadline: December 15, 2018 (or until filled)
* Date posted: November 22, 2018
* Contact: https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/

The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

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

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

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

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

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

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

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

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

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

Responsibilities

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

Requirements

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

Deadline: until December 13, 2018 inclusively

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

Starting date: On or after August 1st, 2019

Application

The application must include the following documents:
* a cover letter
* a curriculum vitæ
* copies of recent publications and research

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

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

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

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

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

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

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

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

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

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

== Software Engineer for Text Mining Applications at the University of Manchester ==

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

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

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

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

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

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

== Assistant Professor, Department of Linguistics, University of Florida ==

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

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

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

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

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

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

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

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

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

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

== Postdoctoral Researcher, Cognitive AI Lab, University of Arizona ==

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

* Employer: Quantitative Criticism Lab, University of Texas at Austin
* Title: Postdoctoral Fellow
* Specialty: Digital humanities and natural language processing
* Location: Austin, TX or remote
* Deadline: October 15, 2018
* Date posted: September 7, 2018
* Contact: https://www.nature.com/naturejobs/science/jobs/652327-postdoctoral-fellow

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

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

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

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

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

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

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

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

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

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

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

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

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

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

== Associate Research Scientist, UKP Lab, TU Darmstadt ==

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: Natural language processing
* Location: Darmstadt
* Deadline: September 30, 2018 (or until filled)
* Date posted: September 6, 2018
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment

The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

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

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

Possible areas of research include, but are not limited to:
* interactive clustering and machine learning to extract sets of textual snippets according to multiple criteria, e.g. high-quality and diverse examples illustrating a lexical entry’s usage;
* NLP for low-resource languages, e.g. analyzing discourse-level argumentation in Georgian;
* interactive sequence labeling to support claim validation by experts, e.g. for extracting evidence from corpora;
* joint text and image processing for content classification in social media, e.g. identifying bias;
* analyzing and generating creative language, such as humor, metaphor, or other rhetorical means.

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

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

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

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

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

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

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

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

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

== Postdoctoral position in natural language understanding, KU Leuven, Belgium ==

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

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

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

'''Responsibilities'''

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

'''Prerequisites'''

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

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

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

'''The research team'''

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

'''The university'''

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

== Postdoctoral position in multilingual text mining, KU Leuven, Belgium ==

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

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

'''Responsibilities'''

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

'''Prerequisites'''

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

'''Offer'''

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

'''Interested'''

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

'''The research team'''

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

'''The university'''

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

== PhD positions in DFG Graduate School AIPHES, TU Darmstadt ==

* Employer: [https://www.aiphes.tu-darmstadt.de/ DFG Graduate School AIPHES], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Doctoral researcher
* Specialty: deep learning, summarization
* Location: Darmstadt
* Deadline: June 27, 2018
* Date posted: June 18, 2018
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment

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

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

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

'''Prerequisites'''

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

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

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

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

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

== Postdoc position: Bocconi University, Milan ==

*Employer: Bocconi University
*Title: Postdoctoral Researcher
*Location: Milan, Italy
*Deadline: June 22nd, 2018, 5 p.m.  
*Starting date: as early as possible, but no later than September 2018
*Duration: 1 year  
*Date Posted: June 18, 2018
*Contact: Paola Cillo (paola.cillo@unibocconi.it)
*URL: https://bit.ly/2JW2tKZ (select the Gucci Lab call)

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

REQUIREMENTS/QUALIFICATIONS  

The successful candidate will work actively on novel directions in deep learning, multi-task learning, and neural networks.  The candidate is expected to have:
* a Ph.D. or equivalent in Computer Science, Computational Linguistics/NLP, Mathematics or related fields.
* Good programming skills in Python.
* Fluent English. Knowledge of other languages is more than welcome.  Knowledge of Italian is NOT a requirement.
* Knowledge of current neural network models, especially Word2Vec and Doc2Vec, and tools for neural networks (e.g. Tensorflow, Keras, PyTorch, etc.).
* Publications in top-tier venues in the field of Computational Linguistics.
* Experience in Ph.D. student supervision is a plus.
* Salary: 43,310.50 euros per annum

HOW TO APPLY  

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

== Postdocs: Johns Hopkins University ==

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

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

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

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

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

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

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

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

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

== Research Fellow in Software Engineering with a Focus on Natural Language Processing at University of Tartu, Estonia ==
* Employer: University of Tartu, Institute of Computer Science, [https://sep.cs.ut.ee/ Software Engineering group]
* Title: Research Fellow
* Speciality: Software engineering, machine learning, natural language processing
* Location: Tartu, Estonia
* Deadline: June 4, 2018
* Date posted: May 21, 2018
* Contact: Dietmar Pfahl, Kairit Sirts (<firstname>.<lastname>@ut.ee)

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

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

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

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

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

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

The deadline for applications is 4 June 2018. The application procedure is outlined in the official advertisement at the [https://www.ut.ee/en/welcome/job-offer/research-fellow-software-engineering-0 University's website].

== Postdoctoral research positions in cybersecurity, natural language processing, and experimental social psychology at SUNY Albany ==
* Employer: University at Albany, Research Foundation of the State University of New York, [http://www.ils.albany.edu/ ILS Institute]
* Title: Postdoctoral researcher
* Speciality: Cybersecurity, natural language processing, machine learning, experimental design
* Location: Albany, New York, USA
* Deadline: July 31, 2018
* Date posted: May 18, 2018
* Contact: Tomek Strzalkowski (tomek {at} albany.edu)

'''Postdoctoral positions''' 

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

'''Requirements for the PANACEA position''' 
For the PANACEA project, we seek a postdoctoral researcher to join our interdisciplinary team. The candidate must have a Ph.D. in Computer Science from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. This position starts September 1, 2018.
* The candidates are expected to have the following skills: in-depth knowledge of current issues and methods in cybersecurity, natural language processing, socio-behavioral computing, human-computer dialogue, statistical methods of data analysis, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with methods of conversational analysis is a plus.

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

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

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

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

'''How to Apply''' 

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

== Two PhD positions in deep learning for natural language understanding and summarisation at Idiap, Switzerland ==
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]
* Title: Two PhD positions
* Speciality: Natural Language Understanding, Summarisation, Machine Learning
* Location: Martigny, Switzerland
* Deadline: May 31, 2018
* Date posted: April 30, 2018
* Contact: James Henderson (james.henderson@idiap.ch)

'''Two PhD positions'''

The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for two PhD student position in the field of natural language understanding, developing deep learning methods for textual entailment and opinion summarisation.

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

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

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

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

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

'''Idiap'''

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

== 2 postdoctoral research positions in text mining and natural language understanding at KU Leuven, Belgium ==
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]
* Title: Postdoctoral researcher
* Speciality: Text mining, natural language understanding, machine learning
* Location: Leuven, Belgium
* Deadline: May 21, 2018
* Date posted: April 23, 2018
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be)

'''Postdoctoral positions''' 

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

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

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

== 2 PhD positions in natural language understanding at KU Leuven, Belgium ==
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]
* Title: PhD researcher
* Speciality: Natural language understanding, machine learning
* Location: Leuven, Belgium
* Deadline: May 21, 2018
* Date posted: April 23, 2018
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be)

'''PhD positions''' 

* PhD position on the topic of multimodal representation learning trained on language and visual data. The goal is to learn continuous representations of language grounded in visual data (static images and video) including the design, implementation and evaluation of novel machine learning architectures that capture textual as well as visual grammars. The learned representations will serve as commonsense knowledge in language understanding tasks. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.

* PhD position on the topic of semantic parsing of natural language sentences and discourse. The goal is to learn compositional models that take into account continuous representations of objects, their attributes and likely relationships. An additional focus is on using the compositional models to efficiently parse language in real-time. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.

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

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

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

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: NLP, machine learning, text mining
* Location: Darmstadt
* Deadline: March 28, 2018
* Date posted: March 19, 2018
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment

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

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

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

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

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

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

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

* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt]
* Title: Doctoral researcher
* Speciality: Natural Language Processing and Machine Learning
* Location: Darmstadt
* Deadline: April 3, 2018
* Date posted: March 19, 2018
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]

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

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

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

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

'''Prerequisites'''

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

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

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

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

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

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

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

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

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

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

'''Optional but preferential''' 

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

'''We offer''' 

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

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

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

Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]

== Postdoctoral position in Psychology at University of Pennsylvania==

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

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

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

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

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

== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==
* Employer: Rochester Institute of Technology
* Title: Postdoctoral Research Scientist
* Specialty: Postdoctoral Research Scientist: Computational Linguistics
* Location: Rochester, New York, United States
* Deadline: Open until filled
* Date posted: February 17, 2018
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]

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

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

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

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

== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==

* Employer: University of Michigan
* Title: Research Fellow
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis
* Location: Ann Arbor, Michigan, United States
* Deadline: March 12, 2018, desired start June 2018
* Date posted: February 12, 2018
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]

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

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

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

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

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

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

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

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

* Employer: University of Colorado Boulder
* Title: Postdoctoral Associate
* Specialty: Machine Learning, Speech and Language Processing
* Location: Boulder, Colorado, United States
* Deadline: Ongoing, desired start August 2018
* Date posted: February 9, 2018
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

== Full-time Researchers, IBM Research - Almaden ==
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]
* Title: Research Staff Member
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas
* Location: San Jose, California, USA
* Deadline: June 1, 2018
* Date posted: January 31, 2018
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)

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

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

The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact.
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174

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

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

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

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

== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==

* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany
* Title: Doctoral researcher
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas
* Location: Darmstadt or Heidelberg
* Deadline: February 11, 2018
* Date posted: January 21, 2018
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]

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

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

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

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

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

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

'''Prerequisites'''

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

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

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

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

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

== Associate Research Scientist, UKP Lab, TU Darmstadt ==

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: Interactive text analysis
* Location: Darmstadt
* Deadline: February 16, 2018
* Date posted: January 21, 2018
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]

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

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

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

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

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

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

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

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

Employment opportunities, postdoctoral positions, summer jobs

2018-12-21T00:27:48Z

Sbowman: Add an NYU postdoc opening.

* '''[[Instructions for Posting Job Ads]]'''
* See also the [http://linguistlist.org/jobs Linguist Job List].
* Archived postings:
** [[Employment opportunities posted 2017|2017]] - [[Employment opportunities posted 2016|2016]] - [[Employment opportunities posted 2015|2015]] - [[Employment opportunities posted 2014|2014]] - [[Employment opportunities posted 2013|2013]] - [[Employment opportunities posted 2012|2012]] - [[Employment opportunities posted 2011|2011]] - [[Employment opportunities posted 2010|2010]] - [[Employment opportunities posted 2009|2009]] - [[Employment opportunities posted 2008|2008]] - [[Employment opportunities posted 2007|2007]]





== Postdoc position, New York University ==
*Employer: Sam Bowman, ML for Language Group, New York University
*Title: Postdoctoral Research Associate
*Speciality: Sentence understanding with neural networks
*Location: New York, NY, USA
*Deadline: Applications will be reviewed until the position is filled, starting the third week of January
*Date posted: December 20, 2018
*Contact: bowman@nyu.edu

For more details, see the NYU ad here: https://apply.interfolio.com/58975

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

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

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

For full consideration, candidates should submit the following materials electronically '''''as a single PDF file''''' to Dr. Yu-Ru Lin at <yuruliny@gmail.com>:
# A brief statement of interest describing your relevant background
# Current CV
# The names and contact information for two references (letters of recommendation will be solicited from finalists)
# Two publications or other writing samples
Please include "PostDoc Application 2019" in the email subject line.

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

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

== Assistant Professor Position at The University of Memphis ==

* Employer: University of Memphis
* Rank or Title: Assistant Professor
* Specialty: ML/NLP with particular interest in educational technologies
* Location: Memphis, Tennessee
* Deadline: 1/7/19 but applications accepted until search completed
* Date Posted: 11/28/18
* Contact email: cconnor2@memphis.edu
* Application link: [https://workforum.memphis.edu/postings/20504]

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

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

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

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

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

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

To apply, please visit [https://workforum.memphis.edu/postings/20504]. Include a cover letter (please include a reference to this position as “CS-IIS”), curriculum vitae, statement of teaching philosophy, research statement, and three letters of recommendation. Direct all inquiries to Corinne O’Connor (cconnor2@memphis.edu).

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

== Research Associate in Text Mining, University of Manchester, UK ==

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

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

Post Objectives:

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

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

3. To develop a classification system for risk assessment.

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

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

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

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

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

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

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

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

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

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

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

== Associate Research Scientist, UKP Lab, TU Darmstadt ==

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: Interactive Text Analysis and Natural Language Processing Tools
* Location: Darmstadt
* Deadline: December 15, 2018 (or until filled)
* Date posted: November 22, 2018
* Contact: https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/

The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

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

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

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

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

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

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

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

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

== Associate Research Scientist, UKP Lab, TU Darmstadt ==

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: Natural language processing
* Location: Darmstadt
* Deadline: December 15, 2018 (or until filled)
* Date posted: November 22, 2018
* Contact: https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/

The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

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

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

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

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

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

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

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

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

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

Responsibilities

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

Requirements

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

Deadline: until December 13, 2018 inclusively

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

Starting date: On or after August 1st, 2019

Application

The application must include the following documents:
* a cover letter
* a curriculum vitæ
* copies of recent publications and research

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

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

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

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

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

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

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

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

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

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

== Software Engineer for Text Mining Applications at the University of Manchester ==

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

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

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

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

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

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

== Assistant Professor, Department of Linguistics, University of Florida ==

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

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

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

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

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

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

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

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

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

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

== Postdoctoral Researcher, Cognitive AI Lab, University of Arizona ==

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

* Employer: Quantitative Criticism Lab, University of Texas at Austin
* Title: Postdoctoral Fellow
* Specialty: Digital humanities and natural language processing
* Location: Austin, TX or remote
* Deadline: October 15, 2018
* Date posted: September 7, 2018
* Contact: https://www.nature.com/naturejobs/science/jobs/652327-postdoctoral-fellow

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

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

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

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

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

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

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

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

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

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

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

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

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

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

== Associate Research Scientist, UKP Lab, TU Darmstadt ==

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: Natural language processing
* Location: Darmstadt
* Deadline: September 30, 2018 (or until filled)
* Date posted: September 6, 2018
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment

The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an

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

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

Possible areas of research include, but are not limited to:
* interactive clustering and machine learning to extract sets of textual snippets according to multiple criteria, e.g. high-quality and diverse examples illustrating a lexical entry’s usage;
* NLP for low-resource languages, e.g. analyzing discourse-level argumentation in Georgian;
* interactive sequence labeling to support claim validation by experts, e.g. for extracting evidence from corpora;
* joint text and image processing for content classification in social media, e.g. identifying bias;
* analyzing and generating creative language, such as humor, metaphor, or other rhetorical means.

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

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

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

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

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

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

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

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

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

== Postdoctoral position in natural language understanding, KU Leuven, Belgium ==

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

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

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

'''Responsibilities'''

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

'''Prerequisites'''

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

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

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

'''The research team'''

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

'''The university'''

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

== Postdoctoral position in multilingual text mining, KU Leuven, Belgium ==

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

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

'''Responsibilities'''

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

'''Prerequisites'''

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

'''Offer'''

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

'''Interested'''

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

'''The research team'''

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

'''The university'''

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

== PhD positions in DFG Graduate School AIPHES, TU Darmstadt ==

* Employer: [https://www.aiphes.tu-darmstadt.de/ DFG Graduate School AIPHES], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Doctoral researcher
* Specialty: deep learning, summarization
* Location: Darmstadt
* Deadline: June 27, 2018
* Date posted: June 18, 2018
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment

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

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

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

'''Prerequisites'''

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

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

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

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

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

== Postdoc position: Bocconi University, Milan ==

*Employer: Bocconi University
*Title: Postdoctoral Researcher
*Location: Milan, Italy
*Deadline: June 22nd, 2018, 5 p.m.  
*Starting date: as early as possible, but no later than September 2018
*Duration: 1 year  
*Date Posted: June 18, 2018
*Contact: Paola Cillo (paola.cillo@unibocconi.it)
*URL: https://bit.ly/2JW2tKZ (select the Gucci Lab call)

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

REQUIREMENTS/QUALIFICATIONS  

The successful candidate will work actively on novel directions in deep learning, multi-task learning, and neural networks.  The candidate is expected to have:
* a Ph.D. or equivalent in Computer Science, Computational Linguistics/NLP, Mathematics or related fields.
* Good programming skills in Python.
* Fluent English. Knowledge of other languages is more than welcome.  Knowledge of Italian is NOT a requirement.
* Knowledge of current neural network models, especially Word2Vec and Doc2Vec, and tools for neural networks (e.g. Tensorflow, Keras, PyTorch, etc.).
* Publications in top-tier venues in the field of Computational Linguistics.
* Experience in Ph.D. student supervision is a plus.
* Salary: 43,310.50 euros per annum

HOW TO APPLY  

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

== Postdocs: Johns Hopkins University ==

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

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

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

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

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

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

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

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

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

== Research Fellow in Software Engineering with a Focus on Natural Language Processing at University of Tartu, Estonia ==
* Employer: University of Tartu, Institute of Computer Science, [https://sep.cs.ut.ee/ Software Engineering group]
* Title: Research Fellow
* Speciality: Software engineering, machine learning, natural language processing
* Location: Tartu, Estonia
* Deadline: June 4, 2018
* Date posted: May 21, 2018
* Contact: Dietmar Pfahl, Kairit Sirts (<firstname>.<lastname>@ut.ee)

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

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

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

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

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

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

The deadline for applications is 4 June 2018. The application procedure is outlined in the official advertisement at the [https://www.ut.ee/en/welcome/job-offer/research-fellow-software-engineering-0 University's website].

== Postdoctoral research positions in cybersecurity, natural language processing, and experimental social psychology at SUNY Albany ==
* Employer: University at Albany, Research Foundation of the State University of New York, [http://www.ils.albany.edu/ ILS Institute]
* Title: Postdoctoral researcher
* Speciality: Cybersecurity, natural language processing, machine learning, experimental design
* Location: Albany, New York, USA
* Deadline: July 31, 2018
* Date posted: May 18, 2018
* Contact: Tomek Strzalkowski (tomek {at} albany.edu)

'''Postdoctoral positions''' 

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

'''Requirements for the PANACEA position''' 
For the PANACEA project, we seek a postdoctoral researcher to join our interdisciplinary team. The candidate must have a Ph.D. in Computer Science from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. This position starts September 1, 2018.
* The candidates are expected to have the following skills: in-depth knowledge of current issues and methods in cybersecurity, natural language processing, socio-behavioral computing, human-computer dialogue, statistical methods of data analysis, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with methods of conversational analysis is a plus.

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

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

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

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

'''How to Apply''' 

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

== Two PhD positions in deep learning for natural language understanding and summarisation at Idiap, Switzerland ==
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]
* Title: Two PhD positions
* Speciality: Natural Language Understanding, Summarisation, Machine Learning
* Location: Martigny, Switzerland
* Deadline: May 31, 2018
* Date posted: April 30, 2018
* Contact: James Henderson (james.henderson@idiap.ch)

'''Two PhD positions'''

The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for two PhD student position in the field of natural language understanding, developing deep learning methods for textual entailment and opinion summarisation.

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

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

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

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

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

'''Idiap'''

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

== 2 postdoctoral research positions in text mining and natural language understanding at KU Leuven, Belgium ==
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]
* Title: Postdoctoral researcher
* Speciality: Text mining, natural language understanding, machine learning
* Location: Leuven, Belgium
* Deadline: May 21, 2018
* Date posted: April 23, 2018
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be)

'''Postdoctoral positions''' 

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

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

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

== 2 PhD positions in natural language understanding at KU Leuven, Belgium ==
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]
* Title: PhD researcher
* Speciality: Natural language understanding, machine learning
* Location: Leuven, Belgium
* Deadline: May 21, 2018
* Date posted: April 23, 2018
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be)

'''PhD positions''' 

* PhD position on the topic of multimodal representation learning trained on language and visual data. The goal is to learn continuous representations of language grounded in visual data (static images and video) including the design, implementation and evaluation of novel machine learning architectures that capture textual as well as visual grammars. The learned representations will serve as commonsense knowledge in language understanding tasks. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.

* PhD position on the topic of semantic parsing of natural language sentences and discourse. The goal is to learn compositional models that take into account continuous representations of objects, their attributes and likely relationships. An additional focus is on using the compositional models to efficiently parse language in real-time. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.

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

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

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

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: NLP, machine learning, text mining
* Location: Darmstadt
* Deadline: March 28, 2018
* Date posted: March 19, 2018
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment

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

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

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

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

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

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

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

* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt]
* Title: Doctoral researcher
* Speciality: Natural Language Processing and Machine Learning
* Location: Darmstadt
* Deadline: April 3, 2018
* Date posted: March 19, 2018
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]

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

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

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

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

'''Prerequisites'''

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

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

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

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

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

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

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

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

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

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

'''Optional but preferential''' 

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

'''We offer''' 

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

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

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

Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]

== Postdoctoral position in Psychology at University of Pennsylvania==

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

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

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

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

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

== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==
* Employer: Rochester Institute of Technology
* Title: Postdoctoral Research Scientist
* Specialty: Postdoctoral Research Scientist: Computational Linguistics
* Location: Rochester, New York, United States
* Deadline: Open until filled
* Date posted: February 17, 2018
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]

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

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

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

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

== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==

* Employer: University of Michigan
* Title: Research Fellow
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis
* Location: Ann Arbor, Michigan, United States
* Deadline: March 12, 2018, desired start June 2018
* Date posted: February 12, 2018
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]

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

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

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

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

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

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

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

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

* Employer: University of Colorado Boulder
* Title: Postdoctoral Associate
* Specialty: Machine Learning, Speech and Language Processing
* Location: Boulder, Colorado, United States
* Deadline: Ongoing, desired start August 2018
* Date posted: February 9, 2018
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

== Full-time Researchers, IBM Research - Almaden ==
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]
* Title: Research Staff Member
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas
* Location: San Jose, California, USA
* Deadline: June 1, 2018
* Date posted: January 31, 2018
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)

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

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

The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact.
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174

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

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

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

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

== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==

* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany
* Title: Doctoral researcher
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas
* Location: Darmstadt or Heidelberg
* Deadline: February 11, 2018
* Date posted: January 21, 2018
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]

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

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

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

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

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

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

'''Prerequisites'''

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

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

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

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

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

== Associate Research Scientist, UKP Lab, TU Darmstadt ==

* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Associate Research Scientist
* Specialty: Interactive text analysis
* Location: Darmstadt
* Deadline: February 16, 2018
* Date posted: January 21, 2018
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]

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

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

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

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

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

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

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

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

Employment opportunities, postdoctoral positions, summer jobs

2017-09-15T15:21:05Z

Sbowman: New postdoc ad from NYU

Textual Entailment Resource Pool

2017-05-29T15:31:41Z

Sbowman: /* RTE data sets */ Adding MultiNLI

[[Textual Entailment]] > '''Resources''':
----

[[Textual Entailment|Textual entailment]] systems rely on many different types of [[Natural Language Processing|NLP]] resources, including term banks, paraphrase lists, parsers, named-entity recognizers, etc. With so many resources being continuously released and improved, it can be difficult to know which particular resource to use when developing a system.

In response, the [[Recognizing Textual Entailment|Recognizing Textual Entailment (RTE)]] shared task community initiated a new activity for building this ''Textual Entailment Resource Pool''. RTE participants and any other member of the NLP community are encouraged to contribute to the pool.

In an effort to determine the relative impact of the resources, RTE participants are strongly encouraged to report, whenever possible, the contribution to the overall performance of each utilized resource. Formal qualitative and quantitative results should be included in a separate section of the system report as well as posted on the talk pages of this Textual Entailment Resource Pool.

'''Adding''' a new resource is very easy. See how to '''use existing templates''' to do this in [[Help:Using Templates]].

== Complete RTE Systems ==

* [http://project.cgm.unive.it/html/venses.html VENSES] (from Ca' Foscari University of Venice, Italy)
* [http://svn.ask.it.usyd.edu.au/trac/candc/wiki/nutcracker Nutcracker] (available for download)
* [http://l2r.cs.uiuc.edu/~cogcomp/kindleDemo.php Entailment Demo] (from the University of Illinois at Urbana-Champaign) - INACTIVE (as of 2010-12-22)
* [http://edits.fbk.eu/ EDITS - Edit Distance Textual Entailment Suite] (open source software developed by [http://hlt.fbk.eu/ Human Language Technology (HLT) group at FBK-Irst])
* [http://u.cs.biu.ac.il/~nlp/downloads/biutee/protected-biutee.html BIUTEE] - Bar Ilan University Textual Entailment Engine (open source)
* [http://hltfbk.github.io/Excitement-Open-Platform/ EXCITEMENT Open Platform (EOP)] - A generic multi-lingual platform for textual inference made available to the scientific and technological communities by the [https://sites.google.com/site/excitementproject/ EU project EXCITEMENT]
* [http://kmcs.nii.ac.jp/tifmo/ TIFMO] (from National Institute of Informatics, Japan)

== RTE data sets ==
=== Past campaigns data sets ===
* [http://pascallin.ecs.soton.ac.uk/Challenges/RTE/Datasets RTE1 dataset] - provided by [http://pascallin.ecs.soton.ac.uk PASCAL]
* [http://pascallin.ecs.soton.ac.uk/Challenges/RTE2/Datasets RTE2 dataset] - provided by [http://pascallin.ecs.soton.ac.uk PASCAL]
* [http://pascallin.ecs.soton.ac.uk/Challenges/RTE3/Datasets RTE3 dataset] - provided by [http://pascallin.ecs.soton.ac.uk PASCAL]
* [http://www.nist.gov/tac/data/past/2008/RTE-4.html RTE4 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.nist.gov/tac/data/past/2009/RTE-5.html RTE5 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.nist.gov/tac/data/past/2010/RTE-6_Main_Task.html RTE6 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.nist.gov/tac/2011/RTE/index.html RTE7 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.cs.york.ac.uk/semeval-2013/task7/ The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge] at SemEval 2013
* [http://www.nyu.edu/projects/bowman/multinli/ The MultiGenre NLI Corpus] (433k examples, used in the [https://repeval2017.github.io/shared/ RepEval 2017 Shared Task])

=== RTE data sets translated in other languages ===
* [http://www.dfki.de/~neumann/resources/RTE3_DE_V1.2_2013-12-02.zip RTE3 dataset translated in German] - provided by [https://sites.google.com/site/excitementproject/ EXCITEMENT]
* [https://sites.google.com/site/excitementproject/results/RTE3-ITA_V1_2012-10-04.zip RTE3 dataset translated in Italian] - provided by [https://sites.google.com/site/excitementproject/ EXCITEMENT]

=== Other data sets ===
* [http://nlp.stanford.edu/projects/snli The Stanford Natural Language Inference (SNLI) corpus], a 570k example manually-annotated TE dataset with accompanying leaderboard.
* [http://www.coli.uni-saarland.de/projects/salsa/fate FrameNet manually annotated RTE 2006 Test Set.] Provided by [http://www.coli.uni-saarland.de/projects/salsa/ SALSA project, Saarland University.]
* [http://www.cs.biu.ac.il/~nlp/files/RTE_2006_Aligned.zip Manually Word Aligned RTE 2006 Data Sets.] Provided by [http://research.microsoft.com/nlp/ the Natural Language Processing Group, Microsoft Research.]
* [http://www-nlp.stanford.edu/projects/contradiction/ RTE data sets annotated for a 3-way decision: entails, contradicts, unknown.] Provided by Stanford NLP Group.
* [http://www.cs.utexas.edu/~pclark/bpi-test-suite/ BPI RTE data set] - 250 pairs, focusing on world knowledge. Provided jointly by [http://www.boeing.com/phantom/math_ct/index.html Boeing], [http://wordnet.cs.princeton.edu/ Princeton], and [http://www.isi.edu ISI].
* [http://hlt.fbk.eu/en/Technology/TE_Specialized_Data Textual Entailment Specialized Data Sets] - 90 RTE-5 Test Set pairs annotated with linguistic phenomena + 203 monothematic pairs (i.e. pairs where only one linguistic phenomenon is relevant to the entailment relation) created from the 90 annotated pairs. Provided jointly by [http://hlt.fbk.eu/en/home FBK-Irst], and [http://www.celct.it/ CELCT].
* [http://www.nist.gov/tac/data/ RTE-5 Search Pilot Data Set annotated with anaphora and coreference information] - RTE-5 Search Data Set annotated with anaphora/coreference information + Augmented RTE-5 Search Data Set, where all the referring expressions which need to be resolved in the entailing sentences are substituted by explicit expressions on the basis of the anaphora/coreference annotation. Provided by [http://www.celct.it/ CELCT] and distributed by [http://www.nist.gov/index.html NIST] at the [http://www.nist.gov/tac/data/ Past TAC Data] web page (2009 Search Pilot, annotated test/dev data).
* [http://www.investigacion.frc.utn.edu.ar/mslabs/~jcastillo/Sagan-test-suite/ RTE-3-Expanded, RTE-4-Expanded, RTE-5-Expanded.] RTE data set expanded in the two and three way task, at least 2000 pairs in each data set.
* [https://agora.cs.illinois.edu/display/rtedata/Explanation+Based+Analysis+of+RTE+Data Explanation-Based Analysis annotation of RTE 5 Main Task subset] described in [http://l2r.cs.uiuc.edu/~danr/Papers/SammonsVyRo10.pdf this ACL 2010 paper]
* [http://art.uniroma2.it/zanzotto/resources/WIKI_FINAL_CORPUS_v1.zip Wiki Entailment Corpus] A RTE-like set of entailment pairs extracted from Wikipedia revisions described in [http://aclweb.org/anthology/W/W10/W10-3504.pdf this paper]
* [https://github.com/daoudclarke/rte-experiment The Guardian Headlines Entailment Training Dataset] An automatically generated dataset of 32,000 pairs similar to the RTE-1 dataset.
* [http://nlp.uned.es/clef-qa/ave/ Answer Validation Exercise at CLEF 2006 (AVE 2006)]
* [http://www.evalita.it/2009/tasks/te The Textual Entailment Task for Italian] at [http://www.evalita.it/2009 EVALITA 2009] An evaluation exercise on TE for Italian.
* [http://www.cs.york.ac.uk/semeval-2012/task8/ Cross-Lingual Textual Entailment for Content Synchronization] The Cross-Lingual Textual Entailment task at [http://www.cs.york.ac.uk/semeval-2012/‎ SemEval 2012].
* [http://www.cs.york.ac.uk/semeval-2013/task8/ Cross-Lingual Textual Entailment for Content Synchronization] The Cross-Lingual Textual Entailment task at [http://www.cs.york.ac.uk/semeval-2013/‎ SemEval 2013].
* [http://nilc.icmc.usp.br/assin/ ASSIN] a shared task on TE for Portuguese with 10,000 pairs.

== Knowledge Resources ==
The [[RTE Knowledge Resources]] page presents:

* a [[RTE Knowledge Resources#Call for Resources|call for resources]], inviting system developers to share the resources used by their own TE engines, to both help improve the TE technology and further test and evaluate such resources;
* [[RTE Knowledge Resources#Ablation tests|the ablation tests]] carried out in the RTE challenges in order to evaluate the impact of knowledge resources and tools on TE system performances;
* [[RTE Knowledge Resources#Publicly available Resources|lists of knowledge resources]], both publicly available and unpublished, used by systems participating in the last RTE challenges.


== Projects ==
* [http://www.cosyne.eu/ CoSyne EU project] The Cross-Lingual Multilingual Content Synchronization with Wikis.
* [https://sites.google.com/site/excitementproject/ EXCITEMENT EU project] EXploring Customer Interactions through Textual EntailMENT.
* [http://qallme.fbk.eu/ QALL-ME EU project] Question Answering Learning technologies in a multiLingual and Multimodal Environment.

== Tools ==

=== Parsers ===
* [http://svn.ask.it.usyd.edu.au/trac/candc C&C parser for Combinatory Categorial Grammar]
* [[Minipar]]
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=SP Shallow Parser] - from the University of Illinois at Urbana-Champaign, see a [http://l2r.cs.uiuc.edu/~cogcomp/shallow_parse_demo.php web demo] of this tool

=== Role Labelling ===
* [http://cemantix.org/assert.html ASSERT]
* [http://www.coli.uni-saarland.de/projects/salsa/shal/ Shalmaneser]
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=SRL Semantic Role Labeler] - from the University of Illinois at Urbana-Champaign, see a [http://l2r.cs.uiuc.edu/~cogcomp/srl-demo.php web demo] of this tool

=== Entity Recognition Tools ===
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=NE Illinois Named Entity Tagger] - see a [http://l2r.cs.uiuc.edu/~cogcomp/ne_demo.php web demo] of this tool
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=CORANKER Illinois Multi-lingual Named Entity Discovery Tool] - see a [http://l2r.cs.uiuc.edu/~cogcomp/ne_matcher_demo.php web demo] of this tool

=== Similarity / Relatedness Tools ===
* [http://ixa2.si.ehu.es/ukb UKB]: Open source [[WordNet]]-based similarity/relatedness tool, includes also pre-computed semantic vectors for all words

=== Corpus Readers ===
* [http://nltk.org NLTK] provides a corpus reader for the data from RTE Challenges 1, 2, and 3 - see the [http://nltk.org/doc/guides/corpus.html#rte Corpus Readers] Guide for more information.

=== Related Libraries ===

* [http://www.semantilog.org/pypes.html PyPES] general purpose library containing evaluation environment for RTE and McPIET text inference engine based on the ERG (English Resource Grammar)

=== Text Normalizers ===
[http://u.cs.biu.ac.il/~nlp/downloads/normalizer.html Java number normalizer (Beta)]
A tool for converting textual representations of numbers to a standard numerical string.

== References ==

*[[Textual Entailment References#Tutorials | Tutorials ]] and [[Textual Entailment References#Workshops | Workshops ]]
*[[Textual Entailment References#Papers in recent conferences and other workshops | Papers in recent conferences and other workshops ]]
*[[Textual Entailment References#Journal papers | Journal papers ]]

== Links ==
* [http://homepages.inf.ed.ac.uk/jbos/rte/ Textual Entailment site by Johan Bos]
* [http://ai-nlp.info.uniroma2.it/research/te/ Textual Entailment at the University of Rome "Tor Vergata"]
[[Category:Textual Entailment Portal]]
* [http://cogcomp.cs.illinois.edu/page/demo_view/18 Illinois Textual Entailment System Component demos]

Textual Entailment References

2017-05-29T15:30:10Z

Sbowman: /* Workshops */ Adding RepEval shared task.

[[Textual Entailment]] > '''References''':
----

''You are welcome to update this list with new papers on textual entailment (please keep the new references in the same format, and maintain the alphabetical order).''

''For challenges and tasks, usually only overview papers are listed. Papers describing systems participating to RTE challenges can be found in the web page of the challenges and tasks.''

=== Tutorials ===

[http://www.esslli2014.info/program/week-one/course-03 Course on Textual Inference at ESSLLI 2014]

[http://jssp2013.fbk.eu/node/4#TE-tutorial JSSP 2013 Tutorial on Textual Entailment, 2013]

[http://fallschool2013.cl.uni-heidelberg.de/course3.mhtml Course on Textual Entailment at the DGfS-CL/EXCITEMENT Fall School 2013]

[http://www.aaai.org/Conferences/AAAI/2013/aaai13tutorials.php#sp4 AAAI 2013 Tutorial on Textual Inference, 2013]

[http://l2r.cs.uiuc.edu/~cogcomp/presentations/RTE_NAACL_2010.zip NAACL 2010 Tutorial on Recognizing Textual Entailment, 2010]

[http://www.cs.biu.ac.il/~dagan/TE-Tutorial-ACL07.ppt ACL 2007 Tutorial on Textual Entailment, 2007]

=== Workshops ===

[https://repeval2017.github.io/ RepEval 2017: The Second Workshop on Evaluating Vector Space Representations for NLP] (featuring a shared task on RTE)

[http://u.cs.biu.ac.il/~nlp/workshop14/index.html Semantic Text Processing Symposium - Industrial Outlook]

[http://jssp2013.fbk.eu/ Joint Symposium on Semantic Processing. Textual Inference and Structures in Corpora]

[http://www.cs.york.ac.uk/semeval-2013/task7/ The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge] at SemEval 2013

[http://www.cs.york.ac.uk/semeval-2013/task8/ Cross-Lingual Textual Entailment for Content Synchronization] The Cross-Lingual Textual Entailment task at [http://www.cs.york.ac.uk/semeval-2013/‎ SemEval 2013].

[http://www.cs.york.ac.uk/semeval-2012/task8/ Cross-Lingual Textual Entailment for Content Synchronization] The Cross-Lingual Textual Entailment task at [http://www.cs.york.ac.uk/semeval-2012/‎ SemEval 2012].

[http://www.nist.gov/tac/2011/RTE/index.html TAC 2011 Recognizing Textual Entailment (RTE) Track (RTE-7), 2011]

[https://sites.google.com/site/textinfer2011/ TextInfer 2011 - Workshop on Textual Entailment, 2011]

[http://www.nist.gov/tac/data/past/2010/RTE-6_Main_Task.html TAC 2010 Recognizing Textual Entailment (RTE) Track (RTE-6), 2010]

[http://www.nist.gov/tac/data/past/2009/RTE-5.html TAC 2009 Recognizing Textual Entailment (RTE) Track (RTE-5), 2009]

[http://art.uniroma2.it/TextInfer2009/index.html TextInfer 2009 - Workshop on Applied Textual Inference, 2009]

[http://www.nist.gov/tac/2008/rte/ TAC 2008 Recognizing Textual Entailment (RTE) Track (RTE-4), 2008]

[http://www.pascal-network.org/Challenges/RTE3/ Third PASCAL Recognising Textual Entailment Challenge (RTE-3), 2007]

[http://www.pascal-network.org/Challenges/RTE2/ Second PASCAL Recognising Textual Entailment Challenge (RTE-2), 2006]

[http://nlp.uned.es/clef-qa/ave/ Answer Validation Exercise at CLEF 2006 (AVE 2006)]

[http://acl.ldc.upenn.edu/W/W05/#W05-1200 ACL 2005 Workshop on Empirical Modeling of Semantic Equivalence and Entailment, 2005]

[http://www.pascal-network.org/Challenges/RTE/ First PASCAL Recognising Textual Entailment Challenge (RTE-1), 2005]

=== Papers in recent conferences and other workshops ===

M. Adler, J. Berant, I. Dagan. 2012. Entailment-based Text Exploration with Application to the Health-care Domain. In Proceedings of the ACL 2012 System Demonstrations.

R. Bar-Haim, I. Dagan, B. Dolan, L. Ferro, D. Giampiccolo, B. Magnini and I. Szpektor. 2006. The Second PASCAL Recognising Textual Entailment Challenge. Proceedings of the Second PASCAL Recognising Textual Entailment Challenge. [http://u.cs.biu.ac.il/~nlp/RTE2/Proceedings/01.pdf pdf]

R. Bar-Haim, I. Dagan, I. Greental and E. Shnarch. 2007. Semantic Inference at the Lexical-Syntactic Level. AAAI 2007. [http://www.aaai.org/Papers/AAAI/2007/AAAI07-138.pdf pdf]

R. Bar-Haim, J. Berant and I. Dagan. 2009. A Compact Forest for Scalable Inference over Entailment and Paraphrase Rules. EMNLP 2009. [http://aclweb.org/anthology//D/D09/D09-1110.pdf pdf]

Marco Baroni, Raffaella Bernardi, Ngoc-Quynh Do, and Chung-chieh Shan. 2012. Entailment above the word level in distributional semantics. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2012), pp. 23–32, Avignon, France. [http://oldsite.aclweb.org/anthology-new/E/E12/E12-1004.pdf pdf]

L. Bentivogli, P. Clark, I. Dagan, D. Giampiccolo. 2011. The Seventh PASCAL Recognizing Textual Entailment Challenge. Proceedings of TAC 2011. [http://www.nist.gov/tac/publications/2011/additional.papers/RTE7_overview.proceedings.pdf pdf]

L. Bentivogli, P. Clark, I. Dagan, D. Giampiccolo. 2010. The Sixth PASCAL Recognizing Textual Entailment Challenge. Proceedings of TAC 2010. [http://www.nist.gov/tac/publications/2010/additional.papers/RTE6_overview.proceedings.pdf pdf]

L. Bentivogli, I. Dagan, H. Dang, D. Giampiccolo, M. Lo Leggio, and B. Magnini . 2009. Considering Discourse References in Textual Entailment Annotation. 5th International Conference on Generative Approaches to the Lexicon (GL 2009). [http://hlt.fbk.eu/sites/hlt.fbk.eu/files/GL2009_Bentivogli-et-al.pdf pdf]

L. Bentivogli, B. Magnini, I. Dagan, H. Dang, D. Giampiccolo. 2009. The Fifth PASCAL Recognizing Textual Entailment Challenge. Proceedings of TAC 2009. [http://www.nist.gov/tac/publications/2009/additional.papers/RTE5_overview.proceedings.pdf pdf]

J. Berant, I. Dagan, M. Adler, J. Goldberger. 2012. Efficient Tree-based Approximation for Entailment Graph Learning. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL 2012).

J. Bos, K. Markert. 2005. Recognising Textual Entailment with Logical Inference. Proceedings of the 2005 Conference on Empirical Methods in Natural Language Processing (EMNLP 2005), pp. 628–635. [http://www.meaningfactory.com/bos/pubs/BosMarkert2005EMNLP.pdf pdf]

R. Braz, R. Girju, V. Punyakanok, D. Roth, and M. Sammons. 2005. An Inference Model for Semantic Entailment in Natural Language. Twentieth National Conference on Artificial Intelligence (AAAI-05)

R. Braz, R. Girju, V. Punyakanok, D. Roth, and M. Sammons. 2005. Knowledge Representation for Semantic Entailment and Question-Answering. IJCAI-05 Workshop on Knowledge and Reasoning for Answering Questions.

E. Cabrio, B. Magnini, A. Ivanova. 2012. Extracting Context-Rich Entailment Rules from Wikipedia Revision History. In Proceedings of the ACL 2012 Workshop on People's Web meets NLP.

C. Corley, A. Csomai and R. Mihalcea. 2005. Text Semantic Similarity, with Applications. RANLP-05.

I. Dagan and O. Glickman. 2004. Probabilistic textual entailment: Generic applied modeling of language variability. In PASCAL Workshop on Learning Methods for Text Understanding and Mining, Grenoble.

I. Dagan, O. Glickman, A. Gliozzo, E. Marmorshtein and C. Strapparava. 2006. Direct Word Sense Matching for Lexical Substitution. COLING-ACL 2006

E. Daya, E. Hurvitz, M. Wasserblat, B. Magnini, G. Neumann, S. Pado, G. Fidanza, G. Gianforme, M. Meisdrock, I. Dagan. 2012. Excitement - EXploring Customer Interactions through Textual EntailMENT. In Proceedings of AVIOS 2012.

R. Delmonte, 2005. VENSES - a Linguistically-Based System for Semantic Evaluation, PLN, Procesamiento del Lenguaje Natural, Revista n° 35, ISSN:1135-5948, pp. 449-450.

R. Delmonte, 2005. Simulare la comprensione del linguaggio con VENSES. presented at Workshop "Scienze Cognitive Applicate", Facolt? di Psicologia dell'Universit? Roma "La Sapienza", 12/13-12-2005.

Georgiana Dinu and Rui Wang. 2009. Inference Rules and their Application to Recognizing Textual Entailment. EACL-09.

M. Dzikovska, R. Nielsen, C. Brew, C. Leacock, D. Giampiccolo, L. Bentivogli, P. Clark, I. Dagan, H. Dang. 2013. SemEval-2013 Task 7: The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge. Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013). [http://aclweb.org/anthology/S/S13/S13-2045 pdf]

P. S. Feizabadi, S. Pado. 2012. Automatic Identification of Motion Verbs in WordNet and FrameNet for Locational Inference. In Proceedings of KONVENS 2012.

M. Geffet and I. Dagan. 2004. Feature Vector Quality and Distributional Similarity. Proceedings of The 20th International Conference on Computational Linguistics (COLING).

M. Geffet and I. Dagan. 2005. "The Distributional Inclusion Hypotheses and Lexical Entailment", ACL 2005, Michigan, USA.

D. Giampiccolo, H. Dang, B. Magnini, I. Dagan, E. Cabrio, B. Dolan. 2008. The Fourth PASCAL Recognizing Textual Entailment Challenge. Proceedings of TAC 2008. [http://www.nist.gov/tac/publications/2008/additional.papers/RTE-4_overview.proceedings.pdf pdf]

O. Glickman, I. Dagan and M. Koppel. 2005. A Probabilistic Classification Approach for Lexical Textual Entailment, Twentieth National Conference on Artificial Intelligence (AAAI-05)

O. Glickman, E. Shnarch and I. Dagan. 2006. Lexical Reference: a Semantic Matching Subtask. EMNLP 2006 (poster).

S. Gorzitze, S. Pado. 2012. Corpus-based Acquisition of German Event- and Object-Denoting Nouns. In Proceedings of KONVENS 2012.

A. Haghighi, A. Y. Ng, and C. D. Manning. 2005. Robust Textual Inference via Graph Matching. HLT-EMNLP 2005.

S. Harabagiu and A. Hickl. 2006. Methods for Using Textual Entailment in Open-Domain Question Answering. COLING-ACL 2006

J. Herrera, A. Peñas, F. Verdejo, 2006. Textual Entailment Recognition Based on Dependency Analysis and WordNet. MLCW 2005. LNAI 3944. 231-239.

V. Jijkoun and M. de Rijke. 2006. Recognizing Textual Entailment: Is Lexical Similarity Enough?, In: I. Dagan, F. Dalche, J. Quinonero Candela, B. Magnini, editors, Evaluating Predictive Uncertainty, Textual Entailment and Object Recognition Systems, LNAI 3944, pages 449-460, Springer Verlag.

L. Kotlerman, I. Dagan, M. Gorodetsky, E. Daya. 2012. Sentence Clustering via Projection over Term Clusters. In Proceedings of *SEM 2012: The First Joint Conference on Lexical and Computational Semantics.

L. Kotlerman, N. Madnani, A. Cahill. 2013. ParaQuery: Making Sense of Paraphrase Collections. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria.

M. Kouylekov and B. Magnini. 2005. Tree Edit Distance for Textual Entailment. RANLP 2005.

Omer Levy, Ido Dagan, and Jacob Goldberger. 2014. Focused Entailment Graphs for Open IE Propositions. In Proceedings of CoNLL 2014.

Omer Levy and Yoav Goldberg. 2014. Linguistic Regularities in Sparse and Explicit Word Representations. In Proceedings of CoNLL 2014.

Omer Levy and Yoav Goldberg. 2014. Dependency-Based Word Embeddings. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014) - Short Papers, Baltimore, Maryland.

O. Levy, T. Zesch, I. Dagan, I. Gurevych. 2013. Recognizing Partial Textual Entailment. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria.

A. Lotan, A. Stern, I. Dagan. 2013. TruthTeller: Annotating Predicate Truth. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

B. MacCartney, T. Grenager, M. de Marneffe, D. Cer and C. D. Manning. 2006. Learning to Recognize Features of Valid Textual Entailments. HLT-NAACL 2006.

B. Magnini, R. Zanoli, I. Dagan, K. Eichler, G. Neumann, T.-G. Noh, S. Pado, A. Stern, O. Levy. 2014. The EXCITEMENT Open Platform for Textual Inferences. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), Baltimore, Maryland.

M. Makatchev, P. W. Jordan, K. Vanlehn. 2004. Abductive Theorem Proving for Analyzing Student Explanations to Guide Feedback in Intelligent Tutoring Systems. Journal of Automated Reasoning, 32(3).

Y. Mehdad, B. Magnini. 2009. A Word Overlap Baseline for the Recognizing Textual Entailment Task. Available at http://hlt.fbk.eu/sites/hlt.fbk.eu/files/baseline.pdf

O. Melamud, I. Dagan, J. Goldberger, I. Szpektor. 2013. Using Lexical Expansion to Learn Inference Rules from Sparse Data. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria.

O. Melamud, J. Berant, I. Dagan, J. Goldberger, I. Szpektor. 2013. A Two Level Model for Context Sensitive Inference Rules. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria.

Oren Melamud, Ido Dagan, Jacob Goldberger, Idan Szpektor and Deniz Yuret. 2014. Probabilistic Modeling of Joint-context in Distributional Similarity. In Proceedings of CoNLL 2014.

Shachar Mirkin, Ido Dagan, Maayan Geffet. 2006. Integrating Pattern-based and Distributional Similarity Methods for Lexical Entailment Acquisition. COLING-ACL 2006 [http://aclweb.org/anthology-new/P/P06/P06-2075.pdf pdf]

Shachar Mirkin, Ido Dagan, Eyal Shnarch. 2009. Evaluating the Inferential Utility of Lexical-Semantic Resources. EACL-09. [http://www.cs.biu.ac.il/~mirkins/publications/Inferential-Utility_Mirkin-DS_EACL09.pdf pdf]

Shachar Mirkin, Lucia Specia, Nicola Cancedda, Ido Dagan, Marc Dymetman and Idan Szpektor. 2009. Source-Language Entailment Modeling for Translating Unknown Terms. ACL-09. [http://www.cs.biu.ac.il/~mirkins/publications/TE4MT_ACL09_Mirkin-Specia-etal.pdf pdf]

Shachar Mirkin, Ido Dagan and Sebastian Padó. 2010. Assessing the Role of Discourse References in Entailment Inference. ACL-10 [http://aclweb.org/anthology-new/P/P10/P10-1123.pdf pdf]

Shachar Mirkin, Jonathan Berant, Ido Dagan and Eyal Shnarch. 2010. Recognising Entailment within Discourse. COLING-10. [http://www.cs.biu.ac.il/~mirkins/publications/Mirkin-etal_COLING-2010.pdf pdf]

Shachar Mirkin, Ido Dagan, Lili Kotlerman and Idan Szpektor. Classification-based Contextual Preferences. TextInfer 2011 [http://aclweb.org/anthology-new/W/W11/W11-2403.pdf]

A. H. Moin, G. Neumann. 2012. Assisting Bug Triage in Large Open Source Projects Using Approximate String Matching. In Proceedings of the Seventh International Conference on Software Engineering Advances (ICSEA 2012).

C. Monz and M. de Rijke. 2001. Light-Weight Entailment Checking for Computational Semantics, In: P. Blackburn and M. Kohlhase, editors, International workshop on Inference in Computational Semantics (ICoS-3).

R. Nairn, C. Condoravdi, and L. Karttunen. 2006. Computing relative polarity for textual inference. International workshop on Inference in Computational Semantics (ICoS-5).

Vivi Nastase, Carlo Strapparava. 2013. Bridging Languages through Etymology: The case of cross language text categorization. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria.

M. Negri, A. Marchetti, Y. Mehdad, L. Bentivogli, D. Giampiccolo. 2013. Semeval-2013 Task 8: Cross-lingual Textual Entailment for Content Synchronization. Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013). [http://www.aclweb.org/anthology/S13-2005 pdf]

M. Negri, A. Marchetti, Y. Mehdad, L. Bentivogli, D. Giampiccolo. 2012. Semeval-2012 Task 8: Cross-lingual Textual Entailment for Content Synchronization. *SEM 2012: The First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012). [http://www.aclweb.org/anthology/S12-1053 pdf]

Tae-Gil Noh, Sebastian Padó. 2013. Using UIMA to Structure An Open Platform for Textual Entailment. In Proceedings of the 3rd Workshop on Unstructured Information Management Architecture (UIMA@GSCL 2013), Darmstadt, Germany, September 23, 2013.

S. Pado, J. Utt. 2012. A Distributional Memory for German. In Proceedings of the KONVENS 2012 Workshop on recent developments and applications of lexical-semantic resources.

S. Padó, J. Šnajder, B. Zeller. 2013. Derivational Smoothing for Syntactic Distributional Semantics. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria.

M. T. Pazienza, M. Pennacchiotti and F. M. Zanzotto . 2006. Discovering asymmetric entailment relations between verbs using selectional preferences. COLING-ACL 2006

V. Pekar. 2006. Acquisition of Verb Entailment from Text. HLT-NAACL 2006

A. Peñas, A. Rodrigo, F. Verdejo. 2006. SPARTE, a Test Suite for Recognising Textual Entailment in Spanish. Computational Linguistics and Intelligent Text Processing, CICLing 2006. LNCS 3878. 275-286

R. Raina, A. Y. Ng, and C. Manning. 2005. Robust textual inference via learning and abductive reasoning. Twentieth National Conference on Artificial Intelligence (AAAI-05)

M. Regneri, R. Wang. 2012. Using Discourse Information for Paraphrase Extraction. In Proceedings of the 2012 Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning.

L. Romano, M. Kouylekov, I. Szpektor, I. Dagan and A. Lavelli. 2006. Investigating a Generic Paraphrase-based Approach for Relation Extraction. EACL 2006.

V. Rus, A. Graesser and K. Desai. 2005. Lexico-Syntactic Subsumption for Textual Entailment. RANLP 2005.

B. Sacaleanu, G. Neumann. 2012. An Adaptive Framework for Named Entity Combination. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC 2012).

Mark Sammons, Vinod Vydiswaran, and Dan Roth. 2010. Ask not what Textual Entailment can do for you.... ACL-10 [http://l2r.cs.uiuc.edu/~danr/Papers/SammonsVyRo10.pdf pdf]

E. Shnarch, I. Dagan, J. Goldberger. 2012. A Probabilistic Lexical Model for Ranking Textual Inferences. In Proceedings of *SEM 2012: The First Joint Conference on Lexical and Computational Semantics.

E. Shnarch, E. Segal Halevi, J. Goldberger, I. Dagan. 2013. PLIS: a Probabilistic Lexical Inference System. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria.

R. Snow, L. Vanderwende and A. Menezes. 2006. Effectively Using Syntax for Recognizing False Entialment. HLT-NAACL 2006.

Gabriel Stanovsky, Jessica Ficler, Ido Dagan and Yoav Goldberg. 2014. Intermediary Semantic Representation Through Proposition Structures. In Proceedings of the ACL workshop on Semantic Parsing.

A. Stern, R. Stern, I. Dagan, A. Felner. 2012. Efficient Search for Transformation-based Inference. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL 2012).

A. Stern, I. Dagan. 2012. BIUTEE: A Modular Open-Source System for Recognizing Textual Entailment. In Proceedings of the ACL 2012 System Demonstrations.

Asher Stern and Ido Dagan. 2014. Recognizing Implied Predicate-Argument Relationships in Textual Inference. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014) - Short Papers, Baltimore, Maryland.

I. Szpektor, I. Dagan, R. Bar-Haim and J. Goldberger. 2008. Contextual Preferences. ACL 2008

M. Tatu and D. Moldovan. 2005. A Semantic Approach to Recognizing Textual Entailment. HLT-EMNLP 2005.

M. Tatu and D. Moldovan. 2006. A Logic-based Semantic Approach to Recognizing Textual Entailment. COLING-ACL 2006 (poster).

A. Volokh, G. Neumann. 2012. Extending Dependency Treebanks with Good Sentences. In Proceedings of KONVENS 2012.

R. Wang, S. Li. 2012. Constructing a Question Corpus for Textual Semantic Relations. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC 2012).

Rui Wang and Günter Neumann. 2007. Recognizing Textual Entailment Using a Subsequence Kernel Method. AAAI-07.

Rui Wang and Yajing Zhang. 2008. Recognizing Textual Entailment with Temporal Expressions in Natural Language Texts. In Proceedings of the IEEE International Workshop on Semantic Computing and Applications (IWSCA-2008).

Rui Wang and Günter Neumann. 2009. An Accuracy-Oriented Divide-and-Conquer Strategy for Recognizing Textual Entailment. TAC 2008 Workshop - RTE-4.

Rui Wang and Yi Zhang. 2009. Recognizing Textual Relatedness with Predicate-Argument Structures. EMNLP 2009.

H. Weisman; J. Berant; I. Szpektor; I. Dagan. 2012. Learning Verb Inference Rules from Linguistically-Motivated Evidence. In Proceedings of the 2012 Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning.

R. Zanoli and S. Colombo. 2016. A Transformation-driven Approach for Recognizing Textual Entailment. Journal of Natural Language Engineering. [http://dx.doi.org/10.1017/S1351324916000176]

F. M. Zanzotto and A. Moschitti. 2006. Automatic learning of textual entailments with cross-pair similarities. COLING-ACL 2006

N. Zeichner, J. Berant, I. Dagan. 2012. Crowdsourcing Inference-Rule Evaluation. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL 2012).

Britta Zeller and Sebastian Padó. 2013. A Search Task Dataset for German Textual Entailment. In Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013).

B. Zeller, J. Šnajder, S. Padó. 2013. DErivBase: Inducing and Evaluating a Derivational Morphology Resource for German. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria.

Torsten Zesch, Omer Levy, Iryna Gurevych, Ido Dagan. 2013. UKP-BIU: Similarity and Entailment Metrics for Student Response Analysis. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013).

Torsten Zesch and Oren Melamud. 2014. Automatic Generation of Challenging Distractors Using Context-Sensitive Inference Rules. In Proceedings of the 9th Workshop on Innovative Use of NLP for Building Educational Applications (BEA).

=== Journal papers ===

I. Androutsopoulos and P. Malakasiotis. 2010. A Survey of Paraphrasing and Textual Entailment Methods. Journal of Artificial Intelligence Research, vol. 38, pp. 135-187. [http://www.jair.org/papers/paper2985.html]

Roy Bar-Haim, Ido Dagan and Jonathan Berant. 2015. Knowledge-Based Textual Inference via Parse-Tree Transformations. Journal of Artificial Intelligence Research, vol. 54, pp 1-57. [http://www.jair.org/papers/paper4584.html]

Elena Cabrio and Bernardo Magnini. 2013. Decomposing Semantic Inferences. LILT - Linguistic Issues in Language Technology, Special issue on Semantic Inferences, volume 9, CSLI Publications.

Ido Dagan, Bill Dolan, Bernardo Magnini and Dan Roth. 2009. Recognizing Textual Entailment: Rational, Evaluation and Approaches. Journal of Natural Language Engineering, vol. 15(4), pp. i-xvii.

Alejandro Figueroa and Günter Neumann. 2014. Category-specific models for ranking effective paraphrases in community Question Answering. Expert Systems With Applications, Volume 41, Issue 10, August 2014, Pages 4730–4742.

Lili Kotlerman, Ido Dagan, Bernardo Magnini, and Luisa Bentivogli. forthcoming. Textual Entailment Graphs. To appear in Journal of Natural Language Engineering, Special Issue on Graphs for NLP.

Lili Kotlerman, Ido Dagan, Idan Szpektor, and Maayan Zhitomirsky-Geffet. 2010. Directional distributional similarity for lexical inference. Journal of Natural Language Engineering, 16(4), 359-389. [http://u.cs.biu.ac.il/~dagan/publications/directional-distsim.pdf pdf]

S. Pado, T.-G. Noh, A. Stern, R. Wang, R. Zanoli. 2014. Design and Realization of a Modular Architecture for Textual Entailment. Journal of Natural Language Engineering, Cambridge University Press.

Asher Stern and Ido Dagan. 2013. The BIUTEE Research Platform for Transformation-based Textual Entailment Recognition. LILT - Linguistic Issues in Language Technology, Special issue on Semantic Inferences, volume 9, CSLI Publications.

Peter D. Turney and Saif M. Mohammad. 2014. Experiments with three approaches to recognizing lexical entailment. Journal of Natural Language Engineering, in press. [http://arxiv.org/abs/1401.8269 pdf]

J. Utt and S. Pado. 2014. Crosslingual and multilingual construction of syntax-based vector space models. Transactions of the Association of Computational Linguistics, volume 2, issue 1. [http://anthology.aclweb.org/Q/Q14/Q14-1020.pdf]

=== Books ===

Ido Dagan, Dan Roth, Mark Sammons and Fabio Massimo Zanzotto. 2013. Recognizing Textual Entailment: Models and Applications. Morgan & Claypool. [http://www.morganclaypool.com/doi/abs/10.2200/S00509ED1V01Y201305HLT023]

[[Category:Textual Entailment Portal]]

Textual Entailment Resource Pool

2016-08-17T10:30:00Z

Sbowman: /* Other data sets */ Reduce link scope.

[[Textual Entailment]] > '''Resources''':
----

[[Textual Entailment|Textual entailment]] systems rely on many different types of [[Natural Language Processing|NLP]] resources, including term banks, paraphrase lists, parsers, named-entity recognizers, etc. With so many resources being continuously released and improved, it can be difficult to know which particular resource to use when developing a system.

In response, the [[Recognizing Textual Entailment|Recognizing Textual Entailment (RTE)]] shared task community initiated a new activity for building this ''Textual Entailment Resource Pool''. RTE participants and any other member of the NLP community are encouraged to contribute to the pool.

In an effort to determine the relative impact of the resources, RTE participants are strongly encouraged to report, whenever possible, the contribution to the overall performance of each utilized resource. Formal qualitative and quantitative results should be included in a separate section of the system report as well as posted on the talk pages of this Textual Entailment Resource Pool.

'''Adding''' a new resource is very easy. See how to '''use existing templates''' to do this in [[Help:Using Templates]].

== Complete RTE Systems ==

* [http://project.cgm.unive.it/html/venses.html VENSES] (from Ca' Foscari University of Venice, Italy)
* [http://svn.ask.it.usyd.edu.au/trac/candc/wiki/nutcracker Nutcracker] (available for download)
* [http://l2r.cs.uiuc.edu/~cogcomp/kindleDemo.php Entailment Demo] (from the University of Illinois at Urbana-Champaign) - INACTIVE (as of 2010-12-22)
* [http://edits.fbk.eu/ EDITS - Edit Distance Textual Entailment Suite] (open source software developed by [http://hlt.fbk.eu/ Human Language Technology (HLT) group at FBK-Irst])
* [http://u.cs.biu.ac.il/~nlp/downloads/biutee/protected-biutee.html BIUTEE] - Bar Ilan University Textual Entailment Engine (open source)
* [http://hltfbk.github.io/Excitement-Open-Platform/ EXCITEMENT Open Platform (EOP)] - A generic multi-lingual platform for textual inference made available to the scientific and technological communities by the [https://sites.google.com/site/excitementproject/ EU project EXCITEMENT]
* [http://kmcs.nii.ac.jp/tifmo/ TIFMO] (from National Institute of Informatics, Japan)

== RTE data sets ==
=== Past campaigns data sets ===
* [http://pascallin.ecs.soton.ac.uk/Challenges/RTE/Datasets RTE1 dataset] - provided by [http://pascallin.ecs.soton.ac.uk PASCAL]
* [http://pascallin.ecs.soton.ac.uk/Challenges/RTE2/Datasets RTE2 dataset] - provided by [http://pascallin.ecs.soton.ac.uk PASCAL]
* [http://pascallin.ecs.soton.ac.uk/Challenges/RTE3/Datasets RTE3 dataset] - provided by [http://pascallin.ecs.soton.ac.uk PASCAL]
* [http://www.nist.gov/tac/data/past/2008/RTE-4.html RTE4 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.nist.gov/tac/data/past/2009/RTE-5.html RTE5 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.nist.gov/tac/data/past/2010/RTE-6_Main_Task.html RTE6 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.nist.gov/tac/2011/RTE/index.html RTE7 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.cs.york.ac.uk/semeval-2013/task7/ The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge] at SemEval 2013

=== RTE data sets translated in other languages ===
* [http://www.dfki.de/~neumann/resources/RTE3_DE_V1.2_2013-12-02.zip RTE3 dataset translated in German] - provided by [https://sites.google.com/site/excitementproject/ EXCITEMENT]
* [https://sites.google.com/site/excitementproject/results/RTE3-ITA_V1_2012-10-04.zip RTE3 dataset translated in Italian] - provided by [https://sites.google.com/site/excitementproject/ EXCITEMENT]

=== Other data sets ===
* [http://nlp.stanford.edu/projects/snli The Stanford Natural Language Inference (SNLI) corpus], a 570k example manually-annotated TE dataset with accompanying leaderboard.
* [http://www.coli.uni-saarland.de/projects/salsa/fate FrameNet manually annotated RTE 2006 Test Set.] Provided by [http://www.coli.uni-saarland.de/projects/salsa/ SALSA project, Saarland University.]
* [http://www.cs.biu.ac.il/~nlp/files/RTE_2006_Aligned.zip Manually Word Aligned RTE 2006 Data Sets.] Provided by [http://research.microsoft.com/nlp/ the Natural Language Processing Group, Microsoft Research.]
* [http://www-nlp.stanford.edu/projects/contradiction/ RTE data sets annotated for a 3-way decision: entails, contradicts, unknown.] Provided by Stanford NLP Group.
* [http://www.cs.utexas.edu/~pclark/bpi-test-suite/ BPI RTE data set] - 250 pairs, focusing on world knowledge. Provided jointly by [http://www.boeing.com/phantom/math_ct/index.html Boeing], [http://wordnet.cs.princeton.edu/ Princeton], and [http://www.isi.edu ISI].
* [http://hlt.fbk.eu/en/Technology/TE_Specialized_Data Textual Entailment Specialized Data Sets] - 90 RTE-5 Test Set pairs annotated with linguistic phenomena + 203 monothematic pairs (i.e. pairs where only one linguistic phenomenon is relevant to the entailment relation) created from the 90 annotated pairs. Provided jointly by [http://hlt.fbk.eu/en/home FBK-Irst], and [http://www.celct.it/ CELCT].
* [http://www.nist.gov/tac/data/ RTE-5 Search Pilot Data Set annotated with anaphora and coreference information] - RTE-5 Search Data Set annotated with anaphora/coreference information + Augmented RTE-5 Search Data Set, where all the referring expressions which need to be resolved in the entailing sentences are substituted by explicit expressions on the basis of the anaphora/coreference annotation. Provided by [http://www.celct.it/ CELCT] and distributed by [http://www.nist.gov/index.html NIST] at the [http://www.nist.gov/tac/data/ Past TAC Data] web page (2009 Search Pilot, annotated test/dev data).
* [http://www.investigacion.frc.utn.edu.ar/mslabs/~jcastillo/Sagan-test-suite/ RTE-3-Expanded, RTE-4-Expanded, RTE-5-Expanded.] RTE data set expanded in the two and three way task, at least 2000 pairs in each data set.
* [https://agora.cs.illinois.edu/display/rtedata/Explanation+Based+Analysis+of+RTE+Data Explanation-Based Analysis annotation of RTE 5 Main Task subset] described in [http://l2r.cs.uiuc.edu/~danr/Papers/SammonsVyRo10.pdf this ACL 2010 paper]
* [http://art.uniroma2.it/zanzotto/resources/WIKI_FINAL_CORPUS_v1.zip Wiki Entailment Corpus] A RTE-like set of entailment pairs extracted from Wikipedia revisions described in [http://aclweb.org/anthology/W/W10/W10-3504.pdf this paper]
* [https://github.com/daoudclarke/rte-experiment The Guardian Headlines Entailment Training Dataset] An automatically generated dataset of 32,000 pairs similar to the RTE-1 dataset.
* [http://nlp.uned.es/clef-qa/ave/ Answer Validation Exercise at CLEF 2006 (AVE 2006)]
* [http://www.evalita.it/2009/tasks/te The Textual Entailment Task for Italian] at [http://www.evalita.it/2009 EVALITA 2009] An evaluation exercise on TE for Italian.
* [http://www.cs.york.ac.uk/semeval-2012/task8/ Cross-Lingual Textual Entailment for Content Synchronization] The Cross-Lingual Textual Entailment task at [http://www.cs.york.ac.uk/semeval-2012/‎ SemEval 2012].
* [http://www.cs.york.ac.uk/semeval-2013/task8/ Cross-Lingual Textual Entailment for Content Synchronization] The Cross-Lingual Textual Entailment task at [http://www.cs.york.ac.uk/semeval-2013/‎ SemEval 2013].

== Knowledge Resources ==
The [[RTE Knowledge Resources]] page presents:

* a [[RTE Knowledge Resources#Call for Resources|call for resources]], inviting system developers to share the resources used by their own TE engines, to both help improve the TE technology and further test and evaluate such resources;
* [[RTE Knowledge Resources#Ablation tests|the ablation tests]] carried out in the RTE challenges in order to evaluate the impact of knowledge resources and tools on TE system performances;
* [[RTE Knowledge Resources#Publicly available Resources|lists of knowledge resources]], both publicly available and unpublished, used by systems participating in the last RTE challenges.


== Projects ==
* [http://www.cosyne.eu/ CoSyne EU project] The Cross-Lingual Multilingual Content Synchronization with Wikis.
* [https://sites.google.com/site/excitementproject/ EXCITEMENT EU project] EXploring Customer Interactions through Textual EntailMENT.
* [http://qallme.fbk.eu/ QALL-ME EU project] Question Answering Learning technologies in a multiLingual and Multimodal Environment.

== Tools ==

=== Parsers ===
* [http://svn.ask.it.usyd.edu.au/trac/candc C&C parser for Combinatory Categorial Grammar]
* [[Minipar]]
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=SP Shallow Parser] - from the University of Illinois at Urbana-Champaign, see a [http://l2r.cs.uiuc.edu/~cogcomp/shallow_parse_demo.php web demo] of this tool

=== Role Labelling ===
* [http://cemantix.org/assert.html ASSERT]
* [http://www.coli.uni-saarland.de/projects/salsa/shal/ Shalmaneser]
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=SRL Semantic Role Labeler] - from the University of Illinois at Urbana-Champaign, see a [http://l2r.cs.uiuc.edu/~cogcomp/srl-demo.php web demo] of this tool

=== Entity Recognition Tools ===
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=NE Illinois Named Entity Tagger] - see a [http://l2r.cs.uiuc.edu/~cogcomp/ne_demo.php web demo] of this tool
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=CORANKER Illinois Multi-lingual Named Entity Discovery Tool] - see a [http://l2r.cs.uiuc.edu/~cogcomp/ne_matcher_demo.php web demo] of this tool

=== Similarity / Relatedness Tools ===
* [http://ixa2.si.ehu.es/ukb UKB]: Open source [[WordNet]]-based similarity/relatedness tool, includes also pre-computed semantic vectors for all words

=== Corpus Readers ===
* [http://nltk.org NLTK] provides a corpus reader for the data from RTE Challenges 1, 2, and 3 - see the [http://nltk.org/doc/guides/corpus.html#rte Corpus Readers] Guide for more information.

=== Related Libraries ===

* [http://www.semantilog.org/pypes.html PyPES] general purpose library containing evaluation environment for RTE and McPIET text inference engine based on the ERG (English Resource Grammar)

=== Text Normalizers ===
[http://u.cs.biu.ac.il/~nlp/downloads/normalizer.html Java number normalizer (Beta)]
A tool for converting textual representations of numbers to a standard numerical string.

== References ==

*[[Textual Entailment References#Tutorials | Tutorials ]] and [[Textual Entailment References#Workshops | Workshops ]]
*[[Textual Entailment References#Papers in recent conferences and other workshops | Papers in recent conferences and other workshops ]]
*[[Textual Entailment References#Journal papers | Journal papers ]]

== Links ==
* [http://homepages.inf.ed.ac.uk/jbos/rte/ Textual Entailment site by Johan Bos]
* [http://ai-nlp.info.uniroma2.it/research/te/ Textual Entailment at the University of Rome "Tor Vergata"]
[[Category:Textual Entailment Portal]]
* [http://cogcomp.cs.illinois.edu/page/demo_view/18 Illinois Textual Entailment System Component demos]

Textual Entailment Resource Pool

2016-08-17T10:29:31Z

Sbowman: /* Other data sets */ Add SNLI

[[Textual Entailment]] > '''Resources''':
----

[[Textual Entailment|Textual entailment]] systems rely on many different types of [[Natural Language Processing|NLP]] resources, including term banks, paraphrase lists, parsers, named-entity recognizers, etc. With so many resources being continuously released and improved, it can be difficult to know which particular resource to use when developing a system.

In response, the [[Recognizing Textual Entailment|Recognizing Textual Entailment (RTE)]] shared task community initiated a new activity for building this ''Textual Entailment Resource Pool''. RTE participants and any other member of the NLP community are encouraged to contribute to the pool.

In an effort to determine the relative impact of the resources, RTE participants are strongly encouraged to report, whenever possible, the contribution to the overall performance of each utilized resource. Formal qualitative and quantitative results should be included in a separate section of the system report as well as posted on the talk pages of this Textual Entailment Resource Pool.

'''Adding''' a new resource is very easy. See how to '''use existing templates''' to do this in [[Help:Using Templates]].

== Complete RTE Systems ==

* [http://project.cgm.unive.it/html/venses.html VENSES] (from Ca' Foscari University of Venice, Italy)
* [http://svn.ask.it.usyd.edu.au/trac/candc/wiki/nutcracker Nutcracker] (available for download)
* [http://l2r.cs.uiuc.edu/~cogcomp/kindleDemo.php Entailment Demo] (from the University of Illinois at Urbana-Champaign) - INACTIVE (as of 2010-12-22)
* [http://edits.fbk.eu/ EDITS - Edit Distance Textual Entailment Suite] (open source software developed by [http://hlt.fbk.eu/ Human Language Technology (HLT) group at FBK-Irst])
* [http://u.cs.biu.ac.il/~nlp/downloads/biutee/protected-biutee.html BIUTEE] - Bar Ilan University Textual Entailment Engine (open source)
* [http://hltfbk.github.io/Excitement-Open-Platform/ EXCITEMENT Open Platform (EOP)] - A generic multi-lingual platform for textual inference made available to the scientific and technological communities by the [https://sites.google.com/site/excitementproject/ EU project EXCITEMENT]
* [http://kmcs.nii.ac.jp/tifmo/ TIFMO] (from National Institute of Informatics, Japan)

== RTE data sets ==
=== Past campaigns data sets ===
* [http://pascallin.ecs.soton.ac.uk/Challenges/RTE/Datasets RTE1 dataset] - provided by [http://pascallin.ecs.soton.ac.uk PASCAL]
* [http://pascallin.ecs.soton.ac.uk/Challenges/RTE2/Datasets RTE2 dataset] - provided by [http://pascallin.ecs.soton.ac.uk PASCAL]
* [http://pascallin.ecs.soton.ac.uk/Challenges/RTE3/Datasets RTE3 dataset] - provided by [http://pascallin.ecs.soton.ac.uk PASCAL]
* [http://www.nist.gov/tac/data/past/2008/RTE-4.html RTE4 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.nist.gov/tac/data/past/2009/RTE-5.html RTE5 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.nist.gov/tac/data/past/2010/RTE-6_Main_Task.html RTE6 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.nist.gov/tac/2011/RTE/index.html RTE7 dataset] - provided by [http://www.nist.gov/index.html NIST] - freely available upon request. For details see [http://www.nist.gov/tac/data/forms/index.html TAC User Agreements]
* [http://www.cs.york.ac.uk/semeval-2013/task7/ The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge] at SemEval 2013

=== RTE data sets translated in other languages ===
* [http://www.dfki.de/~neumann/resources/RTE3_DE_V1.2_2013-12-02.zip RTE3 dataset translated in German] - provided by [https://sites.google.com/site/excitementproject/ EXCITEMENT]
* [https://sites.google.com/site/excitementproject/results/RTE3-ITA_V1_2012-10-04.zip RTE3 dataset translated in Italian] - provided by [https://sites.google.com/site/excitementproject/ EXCITEMENT]

=== Other data sets ===
* [http://nlp.stanford.edu/projects/snli The Stanford Natural Language Inference (SNLI) corpus, a 570k example manually-annotated TE dataset with accompanying leaderboard.]
* [http://www.coli.uni-saarland.de/projects/salsa/fate FrameNet manually annotated RTE 2006 Test Set.] Provided by [http://www.coli.uni-saarland.de/projects/salsa/ SALSA project, Saarland University.]
* [http://www.cs.biu.ac.il/~nlp/files/RTE_2006_Aligned.zip Manually Word Aligned RTE 2006 Data Sets.] Provided by [http://research.microsoft.com/nlp/ the Natural Language Processing Group, Microsoft Research.]
* [http://www-nlp.stanford.edu/projects/contradiction/ RTE data sets annotated for a 3-way decision: entails, contradicts, unknown.] Provided by Stanford NLP Group.
* [http://www.cs.utexas.edu/~pclark/bpi-test-suite/ BPI RTE data set] - 250 pairs, focusing on world knowledge. Provided jointly by [http://www.boeing.com/phantom/math_ct/index.html Boeing], [http://wordnet.cs.princeton.edu/ Princeton], and [http://www.isi.edu ISI].
* [http://hlt.fbk.eu/en/Technology/TE_Specialized_Data Textual Entailment Specialized Data Sets] - 90 RTE-5 Test Set pairs annotated with linguistic phenomena + 203 monothematic pairs (i.e. pairs where only one linguistic phenomenon is relevant to the entailment relation) created from the 90 annotated pairs. Provided jointly by [http://hlt.fbk.eu/en/home FBK-Irst], and [http://www.celct.it/ CELCT].
* [http://www.nist.gov/tac/data/ RTE-5 Search Pilot Data Set annotated with anaphora and coreference information] - RTE-5 Search Data Set annotated with anaphora/coreference information + Augmented RTE-5 Search Data Set, where all the referring expressions which need to be resolved in the entailing sentences are substituted by explicit expressions on the basis of the anaphora/coreference annotation. Provided by [http://www.celct.it/ CELCT] and distributed by [http://www.nist.gov/index.html NIST] at the [http://www.nist.gov/tac/data/ Past TAC Data] web page (2009 Search Pilot, annotated test/dev data).
* [http://www.investigacion.frc.utn.edu.ar/mslabs/~jcastillo/Sagan-test-suite/ RTE-3-Expanded, RTE-4-Expanded, RTE-5-Expanded.] RTE data set expanded in the two and three way task, at least 2000 pairs in each data set.
* [https://agora.cs.illinois.edu/display/rtedata/Explanation+Based+Analysis+of+RTE+Data Explanation-Based Analysis annotation of RTE 5 Main Task subset] described in [http://l2r.cs.uiuc.edu/~danr/Papers/SammonsVyRo10.pdf this ACL 2010 paper]
* [http://art.uniroma2.it/zanzotto/resources/WIKI_FINAL_CORPUS_v1.zip Wiki Entailment Corpus] A RTE-like set of entailment pairs extracted from Wikipedia revisions described in [http://aclweb.org/anthology/W/W10/W10-3504.pdf this paper]
* [https://github.com/daoudclarke/rte-experiment The Guardian Headlines Entailment Training Dataset] An automatically generated dataset of 32,000 pairs similar to the RTE-1 dataset.
* [http://nlp.uned.es/clef-qa/ave/ Answer Validation Exercise at CLEF 2006 (AVE 2006)]
* [http://www.evalita.it/2009/tasks/te The Textual Entailment Task for Italian] at [http://www.evalita.it/2009 EVALITA 2009] An evaluation exercise on TE for Italian.
* [http://www.cs.york.ac.uk/semeval-2012/task8/ Cross-Lingual Textual Entailment for Content Synchronization] The Cross-Lingual Textual Entailment task at [http://www.cs.york.ac.uk/semeval-2012/‎ SemEval 2012].
* [http://www.cs.york.ac.uk/semeval-2013/task8/ Cross-Lingual Textual Entailment for Content Synchronization] The Cross-Lingual Textual Entailment task at [http://www.cs.york.ac.uk/semeval-2013/‎ SemEval 2013].

== Knowledge Resources ==
The [[RTE Knowledge Resources]] page presents:

* a [[RTE Knowledge Resources#Call for Resources|call for resources]], inviting system developers to share the resources used by their own TE engines, to both help improve the TE technology and further test and evaluate such resources;
* [[RTE Knowledge Resources#Ablation tests|the ablation tests]] carried out in the RTE challenges in order to evaluate the impact of knowledge resources and tools on TE system performances;
* [[RTE Knowledge Resources#Publicly available Resources|lists of knowledge resources]], both publicly available and unpublished, used by systems participating in the last RTE challenges.


== Projects ==
* [http://www.cosyne.eu/ CoSyne EU project] The Cross-Lingual Multilingual Content Synchronization with Wikis.
* [https://sites.google.com/site/excitementproject/ EXCITEMENT EU project] EXploring Customer Interactions through Textual EntailMENT.
* [http://qallme.fbk.eu/ QALL-ME EU project] Question Answering Learning technologies in a multiLingual and Multimodal Environment.

== Tools ==

=== Parsers ===
* [http://svn.ask.it.usyd.edu.au/trac/candc C&C parser for Combinatory Categorial Grammar]
* [[Minipar]]
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=SP Shallow Parser] - from the University of Illinois at Urbana-Champaign, see a [http://l2r.cs.uiuc.edu/~cogcomp/shallow_parse_demo.php web demo] of this tool

=== Role Labelling ===
* [http://cemantix.org/assert.html ASSERT]
* [http://www.coli.uni-saarland.de/projects/salsa/shal/ Shalmaneser]
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=SRL Semantic Role Labeler] - from the University of Illinois at Urbana-Champaign, see a [http://l2r.cs.uiuc.edu/~cogcomp/srl-demo.php web demo] of this tool

=== Entity Recognition Tools ===
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=NE Illinois Named Entity Tagger] - see a [http://l2r.cs.uiuc.edu/~cogcomp/ne_demo.php web demo] of this tool
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=CORANKER Illinois Multi-lingual Named Entity Discovery Tool] - see a [http://l2r.cs.uiuc.edu/~cogcomp/ne_matcher_demo.php web demo] of this tool

=== Similarity / Relatedness Tools ===
* [http://ixa2.si.ehu.es/ukb UKB]: Open source [[WordNet]]-based similarity/relatedness tool, includes also pre-computed semantic vectors for all words

=== Corpus Readers ===
* [http://nltk.org NLTK] provides a corpus reader for the data from RTE Challenges 1, 2, and 3 - see the [http://nltk.org/doc/guides/corpus.html#rte Corpus Readers] Guide for more information.

=== Related Libraries ===

* [http://www.semantilog.org/pypes.html PyPES] general purpose library containing evaluation environment for RTE and McPIET text inference engine based on the ERG (English Resource Grammar)

=== Text Normalizers ===
[http://u.cs.biu.ac.il/~nlp/downloads/normalizer.html Java number normalizer (Beta)]
A tool for converting textual representations of numbers to a standard numerical string.

== References ==

*[[Textual Entailment References#Tutorials | Tutorials ]] and [[Textual Entailment References#Workshops | Workshops ]]
*[[Textual Entailment References#Papers in recent conferences and other workshops | Papers in recent conferences and other workshops ]]
*[[Textual Entailment References#Journal papers | Journal papers ]]

== Links ==
* [http://homepages.inf.ed.ac.uk/jbos/rte/ Textual Entailment site by Johan Bos]
* [http://ai-nlp.info.uniroma2.it/research/te/ Textual Entailment at the University of Rome "Tor Vergata"]
[[Category:Textual Entailment Portal]]
* [http://cogcomp.cs.illinois.edu/page/demo_view/18 Illinois Textual Entailment System Component demos]

Research

2016-08-17T10:27:09Z

Sbowman: /* ACL Wiki articles and tutorials */ Add NLI

This page is a list of links to information on research in Computational Linguistics.

* [http://www.aclweb.org/anthology ACL Anthology] - more than 10,000 CL papers
* [[Bibliographies]]
* [[Books]]
* [[Formalisms]]
* [[Papers]]
* [[Resources]]
* [[Searching for papers]]
* [[Wikipedia articles]] - on topics related to Computational Linguistics

== ACL Wiki articles and tutorials ==
Write your own article or tutorial!

* [[Active Learning for NLP]] (stub)
* [[Computational Lexicology]]
* [[Computational Morphology]] (stub)
* [[Computational Phonology]]
* [[Computational Semantics]]
* [[Computational Syntax]]
* [[Constrained Conditional Model]] (stub)
* [[Dialectometrics]]
* [[Dialogue Systems]] (stub)
* [[Distributional Hypothesis]]
* [[Graph Based Methods]] (stub)
* [[Information Extraction]] (stub)
* [[Lexical Acquisition]] (stub)
* [[Machine Translation]] (stub)
* [[Natural Language Generation Portal]]
* [[Natural Language Understanding]] (redirect)
* [[Multiword Expressions]] (stub)
* [[Parsing]] (stub)
* [[Part-of-speech tagging]]
* [[Question Answering]]
* [[Semantics]] (stub)
* [[Speech Processing]]
* [[Statistical Semantics]]
* [[Text Categorization]]
* [[Textual Entailment|Textual Entailment and Natural Language Inference]]
* [[Text Summarization]] (stub)
* [[Training the C&C Parser]]
* [[Word Sense Disambiguation]]


[[Category:Research|*]]

People

2016-08-17T10:24:57Z

Sbowman: /* B */ Add self.

This is a list of homepages of researchers in Computational Linguistics, in the form '''last name, first name - affiliation'''.

See also [[Academic genealogy]], the genealogy of people with academic degrees, based on graduate supervisors being 'parents' and their graduate students being 'children'.

== A ==

*[http://littera.deusto.es/prof/abaitua Abaitua, Joseba] - Universidad de Deusto
*[http://tony.abou-assaleh.net Abou-Assaleh, Tony] - Dalhousie University
*[http://www-personal.umich.edu/~ladamic/ Adamic, Lada] - University of Michigan
*[http://www.cond.org/ Adar, Eytan] - University of Washington
*[http://www.dfki.de/~janal/ Alexandersson, Jan] - German Research Center for Artificial Intelligence
*[http://www.ics.uci.edu/~boris Aleksandrovsky, Boris] UC Irvine
*[http://www-scf.usc.edu/~alcazar/ Alcázar, Asier] - University of Southern California
*[http://alfonseca.org/ Alfonseca, Enrique] - Google
*[http://ixa.si.ehu.es/Ixa/Argitalpenak/kidearen_argitalpenak?kidea=1000808989 Alegria, Iñaki] - University of the Basque Country
*[http://www.dfki.de/~janal/ Alexandersson, Jan] German Research Center for Artificial Intelligence
*[http://www.cs.rochester.edu/u/james/ Allen, James] - University of Rochester
*[http://www.dc.fi.udc.es/~alonso/ Alonso, Miguel A.]
*[http://www.linguist.jussieu.fr/~amsili/ Amsili, Pascal] - University of Paris 7 - Denis Diderot
*[http://www.aueb.gr/users/ion/ Androutsopoulos, Ion] - Athens University of Economics and Business
*[http://clwww.essex.ac.uk/~doug/ Arnold, Doug] Univ. of Essex
*[http://www.ai.sri.com/~appelt/ Appelt, Doug ] SRI International
*[http://korpus.dsl.dk/staff/ja/ Asmussen, Jörg] - DSL - Society for Danish Language and Literature, Copenhagen
*[http://www.carleton.ca/~asudeh/ Asudeh, Ash] - Carleton University
*[http://www.coli.uni-sb.de/~tania/ Avgustinova, Tania] - Universität des Saarlandes

== B ==

*[http://www.cs.cmu.edu/~klb Baker, Kathryn] - Carnegie Mellon University
*[http://comp.ling.utexas.edu/jbaldrid/ Baldridge, Jason] - University of Texas at Austin
*[http://www.cs.mu.oz.au/~tim/ Baldwin, Timothy] - University of Melbourne
*[http://www.georgetown.edu/cball/cball.html Ball, Catherine] - Georgetown University
*[http://www.cs.cmu.edu/~banerjee Banerjee, Satanjeev] - Carnegie Mellon University
*[http://www.lsi.upc.es/~batalla Batalla,Jordi Atserias] - UPC, Spain
*[http://www5.informatik.uni-erlangen.de/Personen/batliner/ Batliner, Anton] - Friedrich-Alexander-Universität Erlangen-Nürnberg
*[http://www.dfki.de/~becker Becker, Tilman] - DFKI Saarbruecken, Germany
*[http://faculty.washington.edu/ebender Bender, Emily] - University of Washington
*[http://homepages.infoseek.com/~corpuslinguistics/homepage.html Berber,Tony] Sardinha
*[http://richard.bergmair.eu/ Bergmair, Richard] University of Cambridge
*[http://wortschatz.uni-leipzig.de/~cbiemann/ Biemann, Chris] - University of Leipzig, Germany
*[http://www.dai.ed.ac.uk/students/kimb Binsted, Kim] University of Edinburgh
*[http://www.cs.mu.oz.au/~sb/ Bird, Steven] - University of Melbourne
*[http://seneca.uab.es/filfrirom/Blanco.html Blanco, Xavier] - Autonomous University of Barcelona
*[http://www.pdg.cnb.uam.es/blaschke/personalPage.html Blaschke, Christian]
*[http://www.dcs.shef.ac.uk/~kalina/ Boncheva, Kalina] Univ. of Sheffield]
*[http://www.dcs.shef.ac.uk/~kalina/ Bontcheva, Kalina] - Univ. of Sheffield
*[http://www3.ntu.edu.sg/home/fcbond/ Bond, Francis] - Nanyang Technological University, Singapore
*[http://www.let.rug.nl/bos/ Bos, Johan] - University of Groningen
*[http://www.iro.umontreal.ca/~boufaden/ Boufaden, Narjès] - University of Montreal
*[http://www.let.rug.nl/~gosse Bouma, Gosse] - University of Groningen
*[http://www.nyu.edu/projects/bowman Bowman, Sam] - New York University
*[http://www.di.fc.ul.pt/~ahb/ Branco, Antonio] - University of Lisbon
*[http://www.karlbranting.net Branting, Karl]
*[http://coli.uni-sb.de/~thorsten Brants, Thorsten] - University of Saarland
*[http://www.coli.uni-sb.de/~brawer Brawer, Sascha] - University of the Saarland
*[http://www.cs.cornell.edu/~ebreck Breck, Eric] - Cornell University
*[http://clwww.essex.ac.uk/~andrewb/ Bredenkamp, Andrew]
*[http://www.csse.monash.edu.au/~jwb/ Breen, Jim] - Monash University
*[http://www.cog.jhu.edu/faculty/brent.html Brent,Michael R.] Johns Hopkins University
*[http://www.informatik.uni-leipzig.de/~brewka/ Brewka] - Gerhard, University of Leipzig
*[http://www.xsoft.com/ Breyman, Clark] Xerox Linguistic Technologies
*[http://research.microsoft.com/%7Ebrill/ Brill, Eric] - Microsoft Research
*[http://www.cl.cam.ac.uk/users/ejb/ Briscoe, Ted] - University of Cambridge
*[http://www.dfki.de/~paulb Buitelaar, Paul] - DFKI
*[http://www.cs.utexas.edu/users/razvan/ Bunescu, Razvan] - University of Texas at Austin

== C ==

*[http://www.hinocatv.ne.jp/~price/ Caldwell, Price] - Meisei University
*[http://www.acs.ilstu.edu/faculty/mecalif/calif.htm Califf,Mary Elaine] - Illinois State University
*[http://ilk.uvt.nl/~sander/ Canisius, Sander] - Tilburg University
*[http://www.cis.upenn.edu/~cliff-group/94/carberry.html Carberry, Sandra] - Univ. of Delaware, Univ. of Pennsylvania
*[http://www.cs.cornell.edu/Info/Faculty/Claire_Cardie.html Cardie, Claire] - Cornell University
*[http://www.cogs.susx.ac.uk/lab/nlp/carroll/carroll.html Carroll, John] - University of Sussex
*[http://jones.ling.indiana.edu/~dcavar Cavar, Damir] - Indiana University, Bloomington
*[http://tantek.com/map.html Celik, Tantek] - Technorati
*[http://cer.freeshell.org Cer, Daniel] - University of Colorado at Boulder
*[http://nlp.changwon.ac.kr/~jcha/ Cha, Jeongwon] - Changwon National University
*[http://www.cs.uleth.ca/~chali Chali, Yllias] - University of Lethbridge
*[http://www.cs.brown.edu/people/ec/home.html Charniak, Eugene] - Brown University
*[http://iit-iti.nrc-cnrc.gc.ca/personnel/chen_boxing_e.html Chen, Boxing] - National Research Council
*[http://www.ciscl.unisi.it/persone/chesi.htm Chesi, Cristiano] - CISCL, University of Siena
*[http://www.isi.edu/~chiang Chiang, David] - USC Information Sciences Institute
*[http://www.alphabit.net/Docente/docente_eng.htm Chiari, Isabella] - University "La Sapienza" of Rome
*[http://korterm.kaist.ac.kr/kschoi/ Choi, Key-Sun] - Korea Advanced Institute of Science and Technology
*[http://web.mit.edu/afs/athena.mit.edu/org/l/linguistics/www/chomsky.home.html Chomsky, Noam] - MIT
*[http://research.microsoft.com/users/church/ Church, Kenneth] - Microsoft Research
*[http://www.dcs.shef.ac.uk/~fabio/ Ciravegna, Fabio] - University of Sheffield
*[http://web.comlab.ox.ac.uk/oucl/work/stephen.clark/ Clark, Stephen] - University of Oxford
*[http://compbio.uchsc.edu/Hunter_lab/Cohen Cohen, Kevin Bretonnel] - U. Colorado School of Medicine
*[http://people.csail.mit.edu/u/m/mcollins/public_html/ Collins, Michael] - MIT Computer Science and Artificial Intelligence Laboratory
*[http://www.cl.cam.ac.uk/users/aac10/ Copestake, Ann] - University of Cambridge
*[http://lands.let.kun.nl/TSpublic/coppen Coppen, Peter-Arno] - University of Nijmegen, The Netherlands
*[http://plg.uwaterloo.ca/~gvcormac/ Cormack, Gordon] - University of Waterloo
*[http://www.psych.qub.ac.uk/staff/teaching/cowie/index.aspx Cowie, Roddy] - Queen's University, Belfast
*[http://www.biostat.wisc.edu/~craven/ Craven, Mark] - University of Wisconsin
*[http://www2.ulster.ac.uk/staff/n.creaney.html Creaney, Norman] - University of Ulster
*[http://www.dia.uniroma3.it/~crescenz/ Crescenzi, Valter] - Università Roma Tre
*[http://thor.info.uaic.ro/~dcristea/ Cristea, Dan] - University of Iasi
*[http://www.harlequin.com/ Crowe, Jeremy] - Harlequin Ltd.
*[http://www.dcs.shef.ac.uk/~hamish Cunningham, Hamish] - University of Sheffield
*[http://www-users.cs.york.ac.uk/~jc/ Cussens, James] - University of York

== D ==
*[http://www.clips.uantwerpen.be/~walter/ Daelemans, Walter] - University of Antwerp
*[http://www.cs.biu.ac.il/~dagan/ Dagan, Ido] - Bar Ilan University, Israel
*[http://conversational-technologies.com Dahl, Deborah] - Conversational Technologies
*[http://stl.recherche.univ-lille3.fr/sitespersonnels/dal/index.html Dal, Georgette] - Universite de Lille
*[http://www.ics.mq.edu.au/~rdale Dale, Robert] - Centre for Language Technology, Macquarie University
*[http://www.cs.utah.edu/~hal/ Daumé III, Hal] - University of Utah
*[http://davies-linguistics.byu.edu Davies, Mark] - Brigham Young University
*[http://cs.haifa.ac.il/~edaya Daya, Ezra] - NICE Systems Ltd.
*[http://www.csi.uottawa.ca/~delannoy Delannoy, Jean-Francois] - University of Ottawa
*[http://www.uqtr.uquebec.ca/~delisle/index.html Delisle, Sylvain] UQTR
*[http://comp.ling.utexas.edu/denis Denis, Pascal] - University of Texas at Austin
*[http://www.math.bas.bg/~iad/ Derzhanski, Ivan] - Bulgarian Academy of Sciences
*[http://www.ling.ohio-state.edu/~dm/ Detmar Meurers, Walt] - The Ohio State University Linguistics Dept.
*[http://www.limsi.fr/Individu/devil/ Devillers, Laurence] - LIMSI
*[http://ixa.si.ehu.es/Ixa/Argitalpenak/kidearen_argitalpenak?kidea=1000808994 Díaz de Ilarraza, Arantza] - University of Basque Country
*[http://www.cs.umd.edu/users/bonnie/ Dorr, Bonnie] - University of Maryland
*[http://www.nyu.edu/pages/linguistics/doughert.html Dougherty, Ray] - New York University
*[http://www.ai.sri.com/~dowding Dowding, John] - SRI
*[http://www.pcug.org.au/~jdowling/ Dowling, Jason] PC Users Group ACT Inc., Canberra, Australia

== E ==

*[http://www.uni-bielefeld.de/lili/personen/cebert/ Ebert, Christian] - University of Bielefeld
*[http://www.ims.uni-stuttgart.de/~eckle/ Eckle-Kohler, Judith]
*[http://www.philipedmonds.com/ Edmonds, Philip] - University of Toronto
*[http://cs.jhu.edu/~jason Eisner, Jason] - Johns Hopkins University
*[http://www.cs.bgu.ac.il/~elhadad/ Elhadad, Michael] - Ben-Gurion University of the Negev
*[http://www.cogsci.ed.ac.uk/~marke/ Ellison, T. Mark] - University of Edinburgh
*[http://www.ik.fh-hannover.de/ik/person/ben/ben.htm Endres-Niggemeyer, Brigitte] FH Hannover
*[http://www.sciences.univ-nantes.fr/info/perso/permanents/enguehard/ Enguehard, Chantal] - Laboratoire d'Informatique de Nantes Atlantique
*[http://coli.uni-sb.de/~erbach/ Erbach, Gregor] - Universität des Saarlandes
*[http://nl.ijs.si/et/ Erjavec, Tomaz]
*[http://comp.ling.utexas.edu/erk/ Erk, Katrin] - University of Texas at Austin
*[http://www.cogsci.uni-osnabrueck.de/~severt/ Evert, Stefan] - University of Osnabrück

== F ==

*[http://slt.wcl.ee.upatras.gr/Fakotakis/personal.htm Fakotakis, Nikos] - University of Patras
*[http://www.phon.ucl.ac.uk/home/alex/home.htm Fang, Alex Chengyu] - University College London
*[http://www.purl.org/net/fa Feldman, Anna] - Montclair State University
*[http://wordnet.princeton.edu/~fellbaum/ Fellbaum, Christiane] - Princeton University
*[http://ling.cuc.edu.cn/htliu/feng/feng.htm Feng, Zhiwei] - IAL of China
*[http://staff.science.uva.nl/~raquel/ Fernandez, Raquel] - ILLC, University of Amsterdam
*[http://www.cs.umbc.edu/~finin/ Finin, Tim] - University of Maryland, Baltimore County (UMBC)
*[http://lingo.stanford.edu/dan/ Flickinger, Dan] - CSLI, Stanford University
*[http://www.dlsi.ua.es/~mlf/ Mikel Forcada] - Universitat d'Alacant
*[http://www.cse.ohio-state.edu/~fosler Fosler-Lussier, Eric] - The Ohio State University
*[http://www.coli.uni-saarland.de/~fouvry/ Fouvry, Frederik]
*[http://www.cs.brown.edu/people/hjf/ Fox, Heidi] - Brown University, Metacarta
*[http://www.cs.technion.ac.il/~francez Francez, Nissim] - Technion, Israel
*[http://www.cs.cmu.edu/~ref/ Frederking, Robert] - Carnegie-Mellon University
*[http://www.ee.ust.hk/~pascale/ Fung, Pascale] - Hong Kong University of Science and Technology

== G ==

*[http://www.cs.technion.ac.il/~gabr Gabrilovich, Evgeniy]
*[http://www.dcs.shef.ac.uk/~robertg/ Gaizauskas, Rob] - University of Sheffield
*[http://www.sics.se/~gamback/ Gamback, Bjorn] - Swedish Institute of Computer Science
*[http://www.dai.ed.ac.uk/students/narcisbg Gardella, Narcis Bassols] Univ. of Edinburgh
*[http://www.coli.uni-sb.de/~claire/ Gardent, Claire] Universität des Saarlandes
*[http://www.gelbukh.com/ Gelbukh, Alexander] - CIC-IPN
*[http://www.isi.edu/natural-language/people/germann/ Germann, Ulrich] - ISI
*[https://netfiles.uiuc.edu/girju/index.html Girju, Roxana] - University of Illinois, Urbana-Champaign
*[http://tcc.itc.it/people/giuliano.html Giuliano, Claudio] - ITC-irst
*[http://www.uni-salzburg.at/portal/page?_pageid=425,405845&_dad=portal&_schema=PORTAL Goebl, Hans] - Univeristät Salzburg
*[http://www.cs.ucf.edu/~gomez Gomez, Fernando] ucf
*[http://www.esi.uem.es/~jmgomez Gomez-Hidalgo, Jose-Maria] - UEM
*[http://www.linguistics.ucsb.edu/faculty/stgries/ Gries, Stefan Th.] - UCSB
*[http://cs.nyu.edu/cs/faculty/grishman/ Grishman, Ralph] - New York University
*[http://das-www.harvard.edu/users/faculty/Barbara_Grosz/Barbara_Grosz.html Grosz, Barbara] - Harvard University
*[http://www-ksl.stanford.edu/people/gruber/ Gruber, Tom] - Stanford University
*[http://www.cs.duke.edu/~cig Guinn, Curry I.] - Duke U.
*[http://www.ukp.tu-darmstadt.de/ Gurevych, Iryna] - Darmstadt University of Technology
*[http://www.cs.bilkent.edu.tr/~guvenir/guvenir.html Guvenir, Altay] - Bilkent University

== H ==

*[http://www.swan.ac.uk/french/web-content/staff/p-ten-hacken.html Hacken, Pius ten] - Swansea University
*[http://www.coling.uni-freiburg.de/~hahn/hahn.html Hahn, Udo] - University of Freiburg
*[http://ufal.mff.cuni.cz/~hajic Hajič, Jan] - Charles University in Prague
*[http://www.linkedin.com/in/aaronhan Han, Aaron Li-Feng] - University of Macau
*[http://www.comp.nus.edu.sg/~cuihang Hang, Cui] - National University of Singapore
*[http://www.coli.uni-sb.de/~hansen Hansen-Schirra, Silvia] - Universität des Saarlandes
*[http://renoir.vill.edu/faculty/hardt/html/home.html Hardt, Daniel] Villanova University
*[http://128.147.244.54/dbmi/profile.cfm?ID=23751 Harkema, Henk] - University of Pittsburgh
*[http://pi7.fernuni-hagen.de/hartrumpf/ Hartrumpf, Sven] - University of Hagen, Germany
*[http://www.cis.udel.edu/~harvey/ Harvey, Terry]
*[http://www.linguistik.uni-erlangen.de/~rrh/ Hausser, Roland] - University of Erlangen, Germany
*[http://www.sims.berkeley.edu/~hearst Hearst, Marti] - UC Berkeley
*[http://www.cse.ogi.edu/~heeman Heeman, Peter] - OGI
*[http://homepages.inf.ed.ac.uk/jhender6/ Henderson, James] - University of Edinburgh
*[http://www.asp.ogi.edu/~hynek/ Hermansky, Hynek] - Oregon Graduate Institute of Science and Technology
*[http://www.isi.edu/~ulf/ Hermjakob, Ulf] - USC/ISI
*[http://www.esi.uem.es/~jmgomez/ Hidalgo, José María Gómez] - Universidad Europea de Madrid
*[http://www.ifi.unizh.ch/staff/hess.html Hess, Michael] - Univ. of Zurich, Switzerland
*[http://www.cs.toronto.edu/~gh Hirst, Graeme] - University of Toronto
*[http://www.isi.edu/~hobbs/ Jerry Hobbs] - USC/ISI
*[http://www.cs.cmu.edu/~chogan Hogan, Christopher] - Carnegie-Mellon University
*[http://www.isi.edu/natural-language/people/hovy.html Hovy, Eduard] - ISI
*[http://ist-socrates.berkeley.edu/~jcl2/churen.htm Huang, Chu-Ren] - Academica Sinica
*[http://www.cs.ucf.edu/~hull Hull, Richard] - University of Central Florida
*[http://compbio.uchsc.edu/Hunter_lab/Hunter Hunter, Larry] - U. Colorado School of Medicine
*[http://datamining.typepad.com/data_mining/ Hurst, Matthew] - BuzzMetrics
*[http://ourworld.compuserve.com/homepages/WJHutchins/ Hutchins, John]
*[http://www.cs.pitt.edu/~hwa Hwa, Rebecca] - University of Pittsburgh

== I ==

== J ==

*[http://www.cis.upenn.edu/~cliff-group/94/pjacobs.html Jacobs, Paul] - General Electric
*[http://www.stanford.edu/~tiflo Jaeger, T. Flroian] - Stanford University
*[http://ist.psu.edu/faculty_pages/jjansen/ Jansen, Jim] - Penn State
*[http://www.cs.nyu.edu/~hengji Ji, Heng] - New York University
*[http://www.cog.brown.edu/~mj Johnson, Mark] - Brown University
*[http://www.cogsci.ed.ac.uk/~bernie/ Jones, Bernie] University of Edinburgh
*[http://www.ida.liu.se/~arnjo/ Jönsson, Arne] - Linkoping University

== K ==
*[http://cs.joensuu.fi/~tkakkone Kakkonen, Tuomo] - University of Joensuu
*[http://www.ai.sri.com/~megumi Kameyama, Megumi] - SRI International
*[http://www.comp.nus.edu.sg/~kanmy Kan, Min-Yen] - National University of Singapore
*[http://users.utu.fi/karhumak/ Karhumaki, Juhani] - University of Turku
*[http://www.sics.se/~jussi/ Karlgren, Jussi] - SICS, Sweden
*[http://www2.parc.com/istl/members/karttune/ Karttunen, Lauri]
*[http://elex.amu.edu.pl/ifa/staff/kaszubski.html Kaszubski, Przemysław] - Adam Mickiewicz University
*[http://www.cs.utexas.edu/users/rjkate/ Kate, Rohit J.] - University of Texas at Austin
*[http://www-users.cs.york.ac.uk/~kazakov/ Kazakov, Dimitar] - University of York
*[http://homepages.inf.ed.ac.uk/keller/ Keller, Frank] - University of Edinburgh
*[http://www.cs.dal.ca Keselj, Vlado] Dalhousie University
*[http://www.mabidkhan.com/ Khan, Abid] - University of Peshawar, Pakistan
*[http://www.itri.bton.ac.uk/~Adam.Kilgarriff Kilgarriff, Adam] - University of Brighton
*[http://www.cs.wisc.edu/~sklein/sklein.html Klein, Sheldon] - University of Wisconsin
*[http://www.isi.edu/~knight/ Knight, Kevin] - ISI
*[http://www.ims.uni-stuttgart.de/~kobdani/ Kobdani, Hamidreza] - University of Stuttgart
*[http://www.iccs.inf.ed.ac.uk/~pkoehn/ Koehn, Philipp] - University of Edinburgh
*[http://svenska.gu.se/~svedk Kokkinakis, Dimitrios] - Göteborg University
*[http://www.cs.ualberta.ca/~kondrak/ Kondrak, Grzegorz] - University of Alberta
*[http://www.coli.uni-saarland.de/~kordoni/ Kordoni, Valia] - Universität des Saarlandes
*[http://www.kornai.com/ Kornai, Andras]
*[http://www.ling.helsinki.fi/~koskenni/ Koskenniemi, Kimmo] - University of Helsinki
*[http://users.encs.concordia.ca/~kosseim/ Kosseim, Leila] - Concordia University, Montreal
*[http://www.dlsi.ua.es/~zkozareva/ Kozareva, Zornitsa] - University of Alicante
*[http://dis.tpd.tno.nl/mmts/wessel_kraaij.html Kraaij, Wessel] - TNO
*[http://www-sk.let.uu.nl Krauwer, Steven, ELSNET] - Utrecht University
*[http://external.nj.nec.com/homepages/krovetz/ Krovetz, Robert] NEC
*[http://www.peter-kuehnlein.net/ Kuehnlein, Peter] - University of Groningen
*[http://jones.ling.indiana.edu/~skuebler/ Kuebler, Sandra] - Indiana University, Bloomington
*[http://www.cs.ucd.ie/staff/nick/ Kushmerick, Nicholas] - University College, Dublin

== L ==

*[http://www.ling.gu.se/~lager/ Lager, Torbjörn] - Göteborg University
*[http://www.ict.csiro.au/staff/Andrew.Lampert/ Lampert, Andrew] - CSIRO ICT Centre / Macquarie University
*[http://www.cs.cmu.edu/~ianlane/ Lane, Ian] - Carnegie Mellon University
*[http://hlt.fbk.eu/en/people/lavelli/ Lavelli, Alberto] - FBK-IRST
*[http://www-personal.umich.edu/~jlawler/index.html Lawler, John] - University of Michigan
*[http://nlp.postech.ac.kr/~gblee Lee, Geunbae] - POSTECH
*[http://www.cs.cornell.edu/home/llee Lee, Lillian] - Cornell University
*[http://www.cs.bham.ac.uk/~mgl Lee, Mark] - University of Birmingham
*[http://www.ling.lancs.ac.uk/staff/geoff/geoff.htm Leech, Geoffrey] - Professor LAMEL, Lancaster University, UK
*[http://jochenleidner.com/ Leidner, Jochen L.] - Research Scientist, Thomson Reuters Corporation
*[http://sites.google.com/site/olemon Lemon, Oliver] - Heriot-Watt University
*[http://www.ilc.cnr.it/~lenci/ Lenci, Alessandro] - Università di Pisa
*[http://people.cs.uchicago.edu/~levow/ Levow, Gina-Anne] - University of Chicago
*[http://www.cc.gatech.edu/~baoli/ Li, Baoli] - Georgia Institute of Technology
*[http://www1.i2r.a-star.edu.sg/~hli/ Li, Haizhou] - Institute for Infocomm Research, Singapore
*[http://www.ling.upenn.edu/~myl/ Liberman, Mark] - University of Pennsylvania
*[http://www.isi.edu/~cyl/ Lin, Chin-Yew] USC/ISI
*[http://www.cs.ualberta.ca/~lindek/ Lin, Dekang] - University of Alberta
*[http://htliu.yeah.net/ Liu, Haitao] - Communication University of China
*[http://nlp.ict.ac.cn/~liuqun/index_en.htm Liu, Qun] - Institute of Computing Technology, CAS
*[http://mtgroup.ict.ac.cn/~liuyang/ Liu, Yang] - Institute of Computing Technology, CAS
*[http://ufal.mff.cuni.cz/~lopatkova Lopatková, Markéta] Charles University in Prague
*[http://terra.di.fct.unl.pt/~gpl/ Lopes, Gabriel] New University of Lisbon
*[http://www.langnat.com/~loupy/index-en.html Loupy, Claude de] - Universite de Paris X Nanterre
*[http://www.personal.psu.edu/xxl13 Lu, Xiaofei] - Pennsylvania State University

== M ==

*[http://www.soi.city.ac.uk/~andym/ MacFarlane, Andrew] - City University of London
*[http://www.desilinguist.org Madnani, Nitin] - Educational Testing Service
*[http://www-cs-students.Stanford.EDU/~magerman Magerman, David] - Stanford University
*[http://tcc.itc.it/people/magnini.html Magnini, Bernardo] - ITC-IRST
*[http://www.karacaymalkar.com Malkar, Karacay] - Webportal
*[http://www.rohan.sdsu.edu/~malouf Malouf, Rob] - San Diego State University
*[http://www.sultry.arts.usyd.edu.au/ Manning, Christopher] - University of Sydney
*[http://www.demarcken.org/carl/ de Marcken, Carl] ITA Software
*[http://www.isi.edu/~marcu/ Marcu, Daniel] - USC/ISI
*[http://overstated.net/about Marlow, Cameron] - Yahoo! Research
*[http://www.limsi.fr/Individu/martin/ Martin,Jean-Claude] - LIMSI
*[http://www.yorku.ca/jmason/ Mason, James A.] - York University
*[http://www.ics.mq.edu.au/~mpawel Mazur, Pawel] - Wroclaw University of Technology and Macquarie University
*[http://www.informatics.susx.ac.uk/research/nlp/mccarthy/mccarthy.html McCarthy, Diana] - University of Sussex
*[http://homepages.inf.ed.ac.uk/mmcconvi McConville, Mark] - University of Edinburgh
*[http://alum.mit.edu/www/davidmcdonald/ McDonald, David] - Smart Information Flow Technologies (SIFT)
*[http://www.cs.columbia.edu/~kathy McKeown, Kathy] Columbia University
*[http://www.eecis.udel.edu/~mccoy/ McKoy, Kathy] - University of Delaware
*[http://stp.lingfil.uu.se/~bea Megyesi, B. Beata] - Uppsala University
*[http://cs.nyu.edu/~melamed Melamed, I. Dan] - New York University
*[http://www.gabormelli.com Melli, Gabor] - PredictionWorks Inc.
*[http://www.latl.unige.ch/personal/paola.html Merlo, Paola] - University of Geneva
*[http://www.ling.ohio-state.edu/~dm/ Meurers, Walt Detmar] OH State Linguistics
*[http://www.csse.uwa.edu.au/~fontor/ Midgley, T. Daniel] - University of Western Australia
*[http://www.cs.unt.edu/~rada Mihalcea, Rada] - University of North Texas
*[http://www.cis.upenn.edu/~elenimi/ Miltsakaki, Eleni] - University of Pennsylvania
*[http://www.ics.mq.edu.au/~mariam Milosavljevic, Maria] - Macquarie University
*[http://coli.uni-sb.de/~mineur Mineur, Anne-Marie] University of the Saarland / Utrecht University
*[http://imaginarycartography.com/work.html Minor, Joshua T.] - Cataphora, Inc.
*[http://staff.science.uva.nl/~gilad/ Mishne, Gilad] - University of Amsterdam
*[http://www.wlv.ac.uk/~le1825/main.html Mitkov, Ruslan] - University of Wolverhampton
*[http://www.let.rug.nl/~begona/ Moirón, Begoña Villada] - University of Groningen
*[http://www.ifi.unizh.ch/~molla/ Molla-Aliod, Diego] - University of Zurich
*[http://www.dcs.qmul.ac.uk/~christof/ Monz, Christof] - University of Amsterdam (ILLC)
*[http://www.cs.utexas.edu/users/mooney/ Mooney, Raymond J.] - University of Texas at Austin
*[http://www.signiform.com/erik/ Mueller, Erik] - IBM Research
*[http://www.xn--stefan-mller-klb.net/ Müler, Stefan] - Universität Bremen
*[http://www.ukp.tu-darmstadt.de/people/mueller/ Müller, Christof] - Darmstadt University of Technology
*[http://www.dlsi.ua.es/eines/membre.cgi?id=eng&nom=rafael&tipus=pdi Muñoz, Rafael] - University of Alicante
*[http://www.puran.info Malik, Abbas] - GETALP - LIG, Université de Grenoble

== N ==

*[http://www.cs.utexas.edu/users/ai-lab/people/grad/nahm.html Nahm, Un Yong] - University of Texas, Austin
*[http://www.univ-nancy2.fr/pers/namer/ Namer, Fiammetta] - University of Nancy
*[http://www.lr.pi.titech.ac.jp/~nanno/index.cgi?page=Tomoyuki+NANNO Nanno, Tomoyuki] - Tokyo Institute of Technology
*[http://www.dlsi.ua.es/~borja/ Navarro, Borja] - University of Alicante, Spain
*[http://tcc.itc.it/people/negri.html Negri, Matteo] - ITC-irst
*[http://www.let.rug.nl/~nerbonne Nerbonne, John] - University of Groningen
*[http://cl-www.dfki.uni-sb.de/~neumann Neumann, Guenter] - DFKI, Saarbrücken
*[http://www.comp.nus.edu.sg/~nght Ng, Hwee Tou] - National University of Singapore
*[http://www.hlt.utdallas.edu/~vince Ng, Vincent] - University of Texas at Dallas
*[http://jdpowerwebintelligence.com/ Nicolov, Nicolas] - J.D. Power and Associates, McGraw-Hill
*[http://www.slt.atr.co.jp/~night/ Nightingale, Stephen] - ATR Institute International
*[http://homepages.inf.ed.ac.uk/mnissim/ Nissim, Malvina] - University of Bologna
*[http://www.comp.nus.edu.sg/~niuzheng Niu, Zheng-Yu] - NU Singapore
*[http://w3.msi.vxu.se/~nivre/ Nivre, Joakim] - Växjö University
*[http://www.cs.berkeley.edu/~russell/norvig.html Norvig, Peter]

== O ==

*[http://www.ltg.ed.ac.uk/~jon/ Oberlander, Jon] - U. Edinburgh
*[http://people.sabanciuniv.edu/oflazer/ Oflazer, Kemal] - Sabanci University, Istanbul, Turkey
*[http://www.loa-cnr.it/oltramari.html Oltramari, Alessandro] - Laboratory for Applied Ontology, Italian National Research Council
*[http://www.wlv.ac.uk/~in6093/ Orasan, Constantin] - University of Wolverhampton
*[http://www.bultreebank.org/petya/OsenovaPub.html Osenova, Petya] - Bulgarian Academy of Sciences

== P ==

*[http://cst.dk/patrizia/ Paggio, Patrizia] - University of Copenhagen
*[http://www.slt.atr.co.jp/~kpaik/ Paik, Kyonghee] - ATR Spoken Language Translation Research Laboratories
*[http://www.cs.cornell.edu/People/pabo Pang, Bo] - Cornell University
*[http://verbs.colorado.edu/~mpalmer/ Palmer, Martha] - University of Colorado
*[http://www.isi.edu/~pantel/ Pantel, Patrick] - ISI/University of Southern California
*[http://www.cs.columbia.edu/~becky/ Passonneau, Rebecca] Columbia University and Bellcore
*[http://www.ilsp.gr/homepages/pastra_eng.html/ Pastra, Katerina] Institute for Language and Speech Processing
*[http://www.cs.utah.edu/~sidd Patwardhan, Siddharth] - University of Utah
*[http://www.l2f.inesc-id.pt/~joana/english.html Paulo Pardal] - Joana L²F] - INESC-ID
*[http://perswww.kuleuven.be/yves_peirsman Peirsman, Yves] - University of Leuven
*[http://www.d.umn.edu/~tpederse Pedersen, Ted] - University of Minnesota, Duluth
*[http://ai-nlp.info.uniroma2.it/pennacchiotti Pennacchiotti, Marco] - University of Roma Tor Vergata
*[http://www.perry.com/ Perry, John] - UCLA
*[http://tcc.itc.it/people/pianesi.html Pianesi, Fabio] - ITC-irst
*[http://www.resegone.com/mapb/ Piccolino Boniforti, Marco Aldo] - Rovira i Virgili University
*[http://cswww.essex.ac.uk/staff/poesio Poesio, Massimo] - University of Essex
*[http://www.fas.umontreal.ca/ling/olst/polguereE Polguere, Alain] - Université de Montréal
*[http://fas.sfu.ca/0h/cs/people/Faculty/Popowich/popowich Popowich, Fred] - Simon Fraser University
*[http://nlp.ipipan.waw.pl/~adamp/ Przepiórkowski, Adam] - Polish Academy of Sciences, Warsaw
*[http://www.ling-phil.ox.ac.uk/people/staff/pulman/ Pulman, Stephen] - Oxford University
*[http://www.cs.brandeis.edu/~jamesp Pustejovsky, James] - Brandeis University

== Q ==

== R ==

*[http://www.eecs.umich.edu/~radev/ Radev, Dragomir] - University of Michigan
*[http://www1.cs.columbia.edu/~rambow/ Rambow, Owen] - CCLS, Columbia University
*[http://www.fask.uni-mainz.de/user/rapp Rapp, Reinhard] - Johannes Gutenberg-Universitaet Mainz
*[http://www.cs.buffalo.edu/pub/WWW/faculty/rapaport/rapaport.html Rapaport, William J.] - SUNY Buffalo
*[http://www.cam.sri.com/manny.html Rayner, Manny] SRI International
*[http://www.cis.upenn.edu/~cliff-group/94/lrau.html Rau, Lisa]
*[http://www.comp.lancs.ac.uk/computing/users/paul/ Rayson, Paul] - Lancaster University
*[http://sivareddy.in Reddy, Siva] - University of York, Lexical Computing Ltd, UK
*[http://www.csd.abdn.ac.uk/~ereiter Reiter, Ehud] - University of Aberdeen
*[http://www.dfki.uni-sb.de/~bert Reithinger, Norbert] - Universität des Saarlandes
*[http://www.reitter-it-media.de/ Reitter, David] - University of Edinburgh
*[http://www.ai.mit.edu/~jrennie/ Rennie, Jason] - MIT
*[http://umiacs.umd.edu/~resnik Resnik, Philip] - University of Maryland, College Park
*[http://www.cs.utah.edu/~riloff/ Riloff, Ellen] - University of Utah
*[http://www.cs.rochester.edu/u/ringger/ Ringger, Eric,] - University of Rochester
*[http://www.di.ufpe.br/~jr Robin, Jacques, Federal] - University of Pernambuco, Brazil.
*[http://www.univ-ab.pt/~vjr/ Rocio, Vitor] - Open University, Lisbon
*[http://www.prodrigues.com/ Rodrigues, Paul] - Indiana University, Bloomington
*[http://www.uteroemer.de/ Romer, Ute] University of Hanover
*[http://www.people.cornell.edu/pages/mr249/ Rooth, Mats] - Cornell University
*[http://l2r.cs.uiuc.edu Roth, Dan] - University of Illinois, Urbana-Champaign
*[http://www.public.asu.edu/~droussi/ Roussinov, Dmitri] - Arizona State University
*[http://www.hi.is/~eirikur/ Rögnvaldsson, Eiríkur] - University of Iceland
*[http://www.uteroemer.de/ Römer, Ute] - University of Hanover
*[http://people.csail.mit.edu/arum Rumshisky, Anna] - MIT
*[http://rykov-cl.narod.ru/ Rykov, Vladimir]

== S ==

*[http://coli.uni-sb.de/~christer Samuelsson, Christer] Bell Labs
*[http://ixa.si.ehu.es/Ixa/Argitalpenak/kidearen_argitalpenak?kidea=1000809006 Sarasola, Kepa] - University of the Basque Country
*[http://www.cs.sfu.ca/~anoop/ Sarkar, Anoop] - currently at Simon Fraser University, formerly at University of Pennsylvania
*[http://personalpages.manchester.ac.uk/staff/yutaka.sasaki/ Sasaki, Yutaka] - University of Manchester
*[http://www.cog.jhu.edu/~savova/ Savova, Virginia] - MIT
*[http://www.dei.unipd.it/~satta Satta, Giorgio] University of Padua
*[http://www.dfki.de/~uschaefer Schaefer, Ulrich] - German Research Center for Artificial Intelligence
*[http://www7.informatik.tu-muenchen.de/~scheler Scheler] - Gabriele, TU München
*[http://www.ims.uni-stuttgart.de/~mike/ Schiehlen, Michael] - University of Stuttgart
*[http://www.ims.uni-stuttgart.de/~schmid/ Schmid, Helmut] - University of Stuttgart
*[http://www.kde.cs.uni-kassel.de/schmitz Schmitz, Christoph] - Universität Kassel
*[http://www.schulteimwalde.de/ Schulte im Walde, Sabine] - Institute for Natural Language Processing, University of Stuttgart
*[http://www.ics.mq.edu.au/~rolfs Schwitter, Rolf] - Macquarie University
*[http://www.informatics.sussex.ac.uk/users/drs22/ Scott, Donia] - University of Sussex
*[http://nlp.cs.nyu.edu/sekine Sekine, Satoshi] - New York University
*[http://www.issco.unige.ch/en/staff/seretan/ Seretan, Violeta] - University of Geneva
*[http://sites.google.com/site/khaledshaalan/ Shaalan, Khaled] - Cairo University
*[http://www.cs.man.ac.uk/~shamsbaa/ Shams, Armin] - Metro College of Management Sciences, Manchester
*[http://www.eecs.harvard.edu/~shieber/ Shieber, Stuart] - Harvard University
*[http://mysite.verizon.net/sidner Sidner, Candy] - BAE Systems, AIT
*[http://www.cs.rochester.edu/u/sikorski/ Sikorski, Teresa] - University of Rochester
*[http://www.lingsoft.fi/~silvonen/ Silvonen, Mikko] - Lingsoft, Inc.
*[http://www.bultreebank.org/kivs/ Simov, Kiril] - Bulgarian Academy of Sciences
*[http://ltrc.iiit.net/anil Singh, Anil Kumar] - Language Technologies Research Centre (LTRC), International Institute of Information Technology (IIIT), Hyderabad, India
*[http://www.cs.cmu.edu/~ssitaram/ Sitaram, Sunayana] - Language Technologies Institute, School of Computer Science, Carnegie Mellon University.
*[http://www.utexas.edu/cola/centers/lrc/general/facultyhomes/jonathan.html Slocum, Jonathan] - The University of Texas at Austin
*[http://www.cs.cmu.edu/~nasmith Smith, Noah] - Carnegie Mellon University
*[http://www.cog.jhu.edu/faculty/smolensky.html Smolensky, Paul] - Johns Hopkins University
*[http://www.ccl.umist.ac.uk/harold/ Somers, Harold] UMIST, Manchester
*[http://www.ece.uiuc.edu/faculty/faculty.asp?rws Sproat, Richard] - University of Illinois, Urbana-Champaign
*[http://www.coling.uni-freiburg.de/~staab/staab.html Staab, Steffen] - Freiburg University
*[http://www.humnet.ucla.edu/humnet/linguistics/people/stabler/stabler.htm Stabler, Edward] - UCLA
*[http://slt.wcl.ee.upatras.gr/stamatatos/personal.html Stamatatos, Efstathios] - University of Patras
*[http://www.cs.toronto.edu/~suzanne/ Stevenson, Suzanne] - University of Toronto
*[http://isl.ira.uka.de/~stiefel Stiefelhagen, Rainer] - Universität Karlsruhe
*[http://www.coling.uni-freiburg.de/~strube/strube.html Strube, Michael] - University of Freiburg
*[http://lvs004.googlepages.com Subramaniam, L. Venkata] - IBM India Research Lab
*[http://www.csi.uottawa.ca/~szpak/ Szpakowicz, Stan] - University of Ottawa

== T ==

*[http://www.sfu.ca/~mtaboada Taboada, Maite] - Simon Fraser University
*[http://hnk.ffzg.hr/mt/ Tadic, Marko] - Faculty of Philosophy, University of Zagreb
*[http://www.ling.helsinki.fi/~tapanain Tapanainen, Pasi] - University of Helsinki
*[http://www8.informatik.uni-erlangen.de/inf8/en/thabet.html Thabet, Iman] - University of Erlangen-Nuremberg
*[http://www.siit.tu.ac.th/dirctory/ft_fac/thanaruk.html Theeramunkong, Thanaruk] - Sirindhorn International Institute of Technology, Thammasat University
*[http://www.objs.com/thompson.htm Thompson, Craig] - Object Services and Consulting, Inc.
*[http://www.let.rug.nl/~tiedeman/blog/index.php?category=1 Tiedemann, Jörg] - University of Groningen
*[http://lia.univ-avignon.fr/chercheurs/torres/ Torres-Moreno, Juan-Manuel] - LIA, Université d'Avignon (France)
*[http://tecfa.unige.ch/tecfa-people/traum.html Traum, David] - TECFA, Universite de Geneve
*[http://www.hum.uit.no/a/trond/ Trosterud, Trond] - University of Tromsø
*[http://www.racai.ro/~tufis/ Tufis, Dan] - Research Institute for Artificial Intelligence, Romanian Academy
*[http://www.apperceptual.com/ Turney, Peter] - Allen Institute for Artificial Intelligence, USA

== U ==

*[http://www.coli.uni-sb.de/~hansu Uszkoreit, Hans] - University of the Saarland and DFKI Saarbrücken

== V ==

*[http://www.q-go.com/ van de Burgt, Stan P.] - Q-go.com
*[http://www.ccl.kuleuven.be/~vincent/ccl/ Vandeghinste, Vincent] - K.U.Leuven
*[http://ilk.uvt.nl/~antalb/ van den Bosch, Antal] - Tilburg University
*[http://www.media.mit.edu/~nwv/ Van Dyke, Neil] - MIT Media Lab
*[http://www.let.rug.nl/~vannoord/ van Noord, Gertjan] University of Groningen
*[http://www.ua.es/personal/chelo.vargas Vargas, Chelo Sierra] - Universidad de Alicante
*[http://grid.let.rug.nl/~mettina/ Veenstra, Mettina] University of Groningen
*[http://www.cs.brandeis.edu/~marc/home.html Verhagen, Marc] - Brandeis University
*[http://www.up.univ-mrs.fr/veronis/ Véronis, Jean] - Université de Provence
*[http://www.dlsi.ua.es/~vicedo/vicedo_en.html Vicedo, Jose Luis] - Alicante University
*[http://www.inf.unisinos.br/~renata/ Vieira, Renata] - Universidade do Vale do Rio dos Sinos, Brazil
*[http://www.cl.cam.ac.uk/~av208/ Villavicencio, Aline] - Federal University of Rio Grande do Sul, Brazil
*[http://home.planet.nl/~weiss075/ Vossen, Piek] Irion Technologies
*[http://www.ling.helsinki.fi/~avoutila/ Voutilainen, Atro] - University of Helsinki

== W ==

*[http://www.dfki.de/~wahlster/ Wahlster, Wolfgang] - Universität des Saarlandes
*[http://www.uindy.gr/faculty/cv/wallace_manolis/ Wallace, Manolis] - National Technical University of Athens
*[http://www.cs.cmu.edu/~yww/ Wang, William Yang] - Carnegie Mellon University
*[http://www.nigelward.com/ Ward, Nigel]
*[http://www.ribbitsoft.com/research/watson/index.html Watson, Bruce] Ribbit Soft.
*[http://hiplab.newcastle.edu.au/~pwatters Watters, Paul A. ] U. of Newcastle, Australia
*[http://www.nick-webb.net Webb, Nick] - SUNY Albany
*[http://www.pages.drexel.edu/~rw37/ Weber, Rosina] - Drexel University
*[http://www.ucsc.cmb.ac.lk/People/rw Weerasinghe, Ruvan] - University of Colombo School of Computing
*[http://www.latl.unige.ch/personal/eric_f.html Wehrli, Eric] - University of Geneva
*[http://www.cs.tu-berlin.de/~ww/ Weisweber, Wilhelm] - Technical University of Berlin
*[http://www.ukp.tu-darmstadt.de Weimer, Markus] - University of Technology Darmstadt
*[http://www.cis.upenn.edu/~bonnie Webber, Bonnie Lynn] - University of Pennsylvania
*[http://www.dcs.shef.ac.uk/~yorick Wilks, Yorick] - University of Sheffield
*[http://cs.haifa.ac.il/~shuly Wintner, Shuly] - University of Haifa, Israel
*[http://www.se.cuhk.edu.hk/~kfwong/ Wong, Kam-Fai] - Chinese University of Hong Kong
*[http://explorer.csse.uwa.edu.au/resume Wong, Wilson] - University of Western Australia
*[http://www.cs.utexas.edu/users/ywwong/ Wong, Yuk Wah] - University of Texas at Austin
*[http://www.cs.man.ac.uk/~wroec/ Wroe, Chris] - University of Manchester
*[http://www.cs.ust.hk/faculty/dekai/bio.html Wu, Dekai] - HKUST

== X ==
*[http://faculty.washington.edu/fxia/ Xia, Fei] - University of Washington
*[http://www1.i2r.a-star.edu.sg/~dyxiong/ Xiong, Deyi] - Institute for Infocomm Research, Singapore

== Y ==

*[http://www.cs.helsinki.fi/u/yangarbe/ Yangarber, Roman] - University of Helsinki
*[http://www.cis.upenn.edu/~cliff-group/94/yarowsky.html Yarowsky, David] - University of Pennsylvania
*[http://www.icl.pku.edu.cn/member/yusw/ Yu, Shiwen] - Peking University
*[http://www.denizyuret.com/ Yuret, Deniz] - Koç University

== Z ==

*[http://ufal.mff.cuni.cz/~zabokrtsky Žabokrtský, Zdeněk] - Charles University in Prague
*[http://ai-nlp.info.uniroma2.it/zanzotto Zanzotto, Fabio Massimo] - University of Roma Tor Vergata
*[http://corpling.uis.georgetown.edu/amir Zeldes, Amir] - Georgetown University
*[http://ufal.mff.cuni.cz/~zeman/ Zeman, Dan] - Univerzita Karlova v Praze
*[http://www.ukp.tu-darmstadt.de/ Zesch, Torsten] - Darmstadt University of Technology
*[http://www1.i2r.a-star.edu.sg/~mzhang/ Zhang, Min] - Institute for Infocomm Research, Singapore
*[http://bcmi.sjtu.edu.cn/~zhaohai/ Zhao, Hai] - City University of Hong Kong
*[http://pages.cs.wisc.edu/~jerryzhu/ Zhu, Xiaojin (Jerry)] - University of Wisconsin, Madison
*[http://www.csse.monash.edu.au/~ingrid/ Zukerman, Ingrid] - Monash University