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* '''[[Instructions for Posting Job Ads]]'''
 
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* See also the [http://linguistlist.org/jobs/index.html Linguist Job List].
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* See also the [http://linguistlist.org/jobs Linguist Job List].
 
* Archived postings:
 
* Archived postings:
** [[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]]
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** [[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]]
 
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== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==
  
== Senior Research Scientist - Xerox Research Centre Europe ==
+
* 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]
  
* Employer: Xerox Research Centre Europe (XRCE) http://www.xrce.xerox.com/
+
PhD positions in DFG Graduate School AIPHES: Natural Language  
* Rank or Title: Senior Research Scientist
+
Processing and Computational Linguistics
* Specialty: Statistical Natural Language Processing, Machine Learning
 
* Location: Grenoble, France
 
* Deadline: 31 July 2013 or until position is filled
 
* Date Posted: 2 May 2013
 
* Contact email: James.Henderson@xrce.xerox.com
 
  
'''Position Description'''
+
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 Parsing & Semantics research area at Xerox Research Centre Europe (XRCE) is currently looking for an experienced researcher in statistical natural language processing (NLP), with a deep understanding of machine learning for NLP.  The ideal candidate would have experience or knowledge of parsing, information extraction, weak supervision, textual entailment, and combining machine learning with expert knowledge.  Awareness of the healthcare domain is a plus. The applicant should have a strong publication record and good coding skills. The seniority of the appointment will depend on qualifications.
+
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 successful candidate will be expected to identify challenging problems, develop novel solutions, and work with business and development teams to ensure that these solutions have a significant impact.  Senior researchers are expected to also lead research projects. We work together with top academic partners and expect our researchers to publish results in top-tier conferences and journals. We also have multiple open innovation collaborations with academic partners world-wide.  
+
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.
  
The Parsing & Semantics group concentrates on automatically understanding text using syntactic and semantic analysis. The group focuses on natural language processing methods for robust parsing, semantic analysis, and information discovery, including the role of context in determining meaning. We are particularly interested in statistical models that exploit many sources of information, such as context, corpora, domain knowledge, knowledge bases, and task performance. The Parsing & Semantics group collaborates closely with the Machine Learning for Services group and the Machine Learning for Document Access and Translation group. We are also interested in applying research results to practical applications and real-world problems. Our general application focus is on converting unstructured text into structured information, including facts and opinions.  The solutions we develop play a key role in Xerox's next generation document and business process outsourcing services in domains such as customer care, health care, financial services, and market analysis.
+
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).
  
XRCE is located in Grenoble, France, in the heart of the French Alps. Grenoble offers an excellent quality of life and a large scientific community. For more information, please see http://www.xrce.xerox.com/About-XRCE/Career-opportunities/Senior-Research-Scientist-in-Statistical-Natural-Language-Processing.
+
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.
  
'''Requirements'''
 
  
* PhD in Computer Science or Computational Linguistics
+
'''Prerequisites'''
* NLP knowledge and experience
 
* Machine learning knowledge or experience
 
* Strong publication record
 
* Programming skills
 
* Strong written and oral communications skills in English
 
  
'''Application instructions '''
+
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.
  
Applications will be considered as they are received. To ensure that an application receives full consideration it should be submitted by '''July 31, 2013'''. Applications will be considered beyond this date until the position is filled.
+
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
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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.
  
Informal inquiries can be made to James.Henderson@xrce.xerox.com or Tonya.Love@xerox.com.  
+
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:
  
To submit an application, please send your CV and cover letter to both xrce-candidates@xrce.xerox.com and to Tonya.Love@xerox.com. You should also include in your CV at least three referees we can contact for letters of recommendation.  
+
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.
  
== Internship Opportunities in Qatar Computing Research Institute (QCRI) ==
 
  
* Employer: Qatar Computing Research Institute (http://www.qcri.qa)
+
== Associate Research Scientist, UKP Lab, TU Darmstadt ==
* Rank or Title: Intern/Research associate/Research assistant
 
* Specialty: Information retrieval, text mining, natural language processing
 
* Location: Doha, Qatar
 
* Deadline: May 31, 2013
 
* Date Posted: March 15, 2013
 
* Contact email: kdarwish@qf.org.qa, wmagdy@qf.org.qa, wgao@qf.org.qa
 
  
'''POSITION DESCRIPTION'''
+
* 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 NLP/IR group at the Qatar Computing Research Institute (QCRI) is looking for 3 interns to work on a project that involves the search and visualization of social content (e.g. tweets, Facebook posts and comments). Underlying technologies for the project include information retrieval, text mining, and natural language processing.
+
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of  
 +
Computer Science, Technische Universität (TU) Darmstadt, Germany has
 +
an opening for an
  
'''INTERNSHIP TASKS INCLUDE'''
+
Associate Research Scientist
* Development of effective techniques for information filtering from social media
+
(PostDoc- or PhD-level; for an initial term of two years)
* Diversity analysis, categorization, and summarization of search results
 
* Development of effective techniques for processing the social Arabic/English language for real-time indexing and search
 
* Web design/development of visualization schemes for social search results
 
* Conducting project-related research work supervised by scientists in the team
 
  
'''EXPECTED APPLICANTS SHOULD BE/HAVE'''
+
in the areas of Interactive Text Analysis, the UKP Lab is looking for
* PhD/Master students in computer science or related field
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a researcher with a background in Natural Language Processing and
* At least 1-year research experience
+
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by
* Familiarity with open-source search engines and large-scale text processing (e.g. Lucene, Solr, Casandra, and Hadoop) is desirable.
+
the German Research Foundation (DFG). The project is developing a
* Background in social network analysis and/or natural language processing is a plus
+
comprehensive interactive text analysis platform to improve efficiency
* Basic knowledge of Arabic language can help but is not mandatory
+
and to enable new ways of exploring, annotating and analyzing
* Web development/design experience is essential for one of the positions (fresh graduates are encouraged to apply for this position)
+
large-scale text corpora through the use of assistive features based
 +
on machine-learning.
  
'''INTERNSHIP NATURE'''
+
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.
  
Interns are expected to contribute novel ideas and techniques to the project. The interns will have the opportunity to tap massive amount of data and to release their work in a public facing site. It is highly encouraged to publish the performed research work in top tier conferences. Also, novel ideas are potentially filed as patents.  
+
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.
  
Prospective interns are expected to spend between 3 to 6 months in QCRI. During the period, the intern is provided with free fully-serviced accommodation, a car for transportation (driving license is required), and a competitive tax-free salary paid on a monthly bases. Internship can start anytime during the year.
+
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.
  
'''ABOUT QCRI'''
+
Applications should include a detailed CV, a motivation letter and an
 +
outline of previous working or research experience (if available).
  
Qatar Computing Research Institute (QCRI) was established in 2010 by Qatar Foundation for Education, Science and Community Development (http://www.qf.org.qa), a private, non-profit organization that is supporting Qatar’s transformation from traditionally carbon-based economy to sustainably knowledge-based one.
+
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.
  
QCRI supports Qatar Foundation’s mission by helping to build Qatar’s innovation and technology capacity. It is focused on tackling large-scale computing challenges that address national priorities for growth and development. In doing this, QCRI conducts world-class multidisciplinary computing research that is relevant to the needs of Qatar, the wider Arab region, and the world. We perform cutting-edge research in such areas as Arabic language technologies, social computing, data analytics, distributed/cloud computing and so on. The research work we are conducting at QCRI is aligned with the Qatar National Research Strategy, and supports the strategic priorities outlined in Qatar National Vision 2030.
+
== 3-year research postdoc position in computational social science at Bocconi University, Milan ==
  
'''APPLICATION'''
+
*Employer: Bocconi University, marketing department, supervisor Dirk Hovy
 +
*Title: Postdoc
 +
*Specialty: NLP, neural networks, computational social science
 +
*Location: Milan, Italy
 +
*Starting date: March 1, 2018
 +
*Deadline: Apply by noon January 22, 2018
 +
*Date Posted: December 29, 2017
 +
*Contact: dip.mkt@unibocconi.it
  
Please send CV to kdarwish@qf.org.qa, wmagdy@qf.org.qa, wgao@qf.org.qa. Alternatively, you can apply at http://qcri.qa/join-us/apply-now/apply-now
+
'''Project Title:''' Neural methods for text analysis in the social sciences
  
For more information, please visit:  
+
'''Project Description:''' Text is a common medium in all social sciences, offering insights into human behavior. However, text is complex and encodes many different aspects at the same time. In order to analyze text for social science projects, we need to develop the right tools, based on natural language processing. These tools needs to scale to large amounts of text, allow for exploration and predictive modeling, and allow a multitude of analyses (classification, regression, clustering, etc). Neural-network approaches to NLP have lately demonstrated all of these properties, but have rarely been applied to social science problems. The goal of this project is to establish a baseline in tools and techniques that can be widely applied, and that can form the basis of future research and training.
http://www.qcri.qa
+
The full description of the position and the application details can be found at:
http://qcri.qa/our-research/arabic-language-technologies
+
https://www.unibocconi.eu/wps/wcm/connect/d61571c4-b0cf-4aad-a25c-b963801595bf/Call-ADR-09H1-MKT.pdf?MOD=AJPERES&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An
  
 +
'''Responsibilities:''' The candidate would work predominantly on research, i.e., the implementation and testing of model architectures, data mining and preparation, and dissemination of results. Teaching opportunities (for additional salary) are available.
  
== Postdoctoral fellow -- KU Leuven ==
+
'''Scientific sector:''' 09/H1 Information processing systems
  
* Employer: Department of Computer Science, KU Leuven, Belgium
 
* Rank or Title: Postdoctoral fellow
 
* Specialty: Information extraction, natural language understanding, machine reading
 
* Location: Leuven, Belgium
 
* Deadline: Until position fills
 
* Date Posted: April 13, 2013
 
* Contact email: Sien.Moens@cs.kuleuven.be
 
  
'''Position description'''
 
The Language Intelligence and Information Retrieval group, which is part of the Department of Computer Science at KU Leuven (http://www.cs.kuleuven.be/groups/liir/), has an open postdoctoral position for a motivated researcher with interest and expertise in information extraction from text. The work will be conducted in the framework of the EU FP7 MUSE research project (http://www.muse-project.eu/) granted under the Future and Emerging Technologies ICT call. The candidate is holder of a PhD degree, and can show his or her expertise through several publications in major conferences or journals in the fields of computational linguistics, machine learning and/or artificial intelligence.
 
The position will be for two years starting in the Summer of 2013 or earlier. The candidate has excellent English language skills (written and spoken), good communication skills especially for guiding master and PhD students, good programming skills (e.g., Java, C++, MATLAB, Python) and has the capability to work independently and in a team.
 
  
'''Application instructions '''
 
  
Please send your application to Marie-Francine Moens (Sien.Moens@cs.kuleuven.be).
+
== Teaching Faculty in Human Language Technology: Johns Hopkins University ==
  
 +
*Employer: Johns Hopkins University
 +
*Title: Senior Lecturer, Associate Teaching Professor or Teaching Professor
 +
*Location: Baltimore, MD
 +
*Deadline: Apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled
 +
*Date Posted: December 21, 2017
 +
*Contact: clspsearch@clsp.jhu.edu
  
'''Other considerations'''
+
The Center for Language and Speech Processing (CLSP) at Johns Hopkins University seeks outstanding candidates for a fulltime teaching position. The search is open to all ranks, including Senior Lecturer, Associate Teaching Professor and Teaching Professor.
  
Situated in the heart of Western Europe, KU Leuven has been a centre of learning for almost six centuries. KU Leuven is a research-intensive, internationally oriented university that carries out both fundamental and applied research.  It is strongly inter- and multidisciplinary in focus and strives for international excellence. To this end, KU Leuven works together actively with its research partners at home and abroad.
+
This position will be central to CLSP’s new Certificate in Human Language Technology, part of the master’s degree programs in Computer Science (CS) and the Electrical and Computer Engineering (ECE). The successful candidate will be involved in new course development, graduate teaching, graduate academic advising, supervising master's thesis projects, and managing various aspects of the Certificate program. Although this is primarily a teaching position, there is also potential for research effort.
  
== Post-doctoral fellows -- University of Alberta ==
+
Successful candidates will join the faculty of CLSP, one of the largest and most visible academic organizations in speech processing and NLP. For more than two decades, CLSP has advanced the state of the art in research, hosted international research teams (the annual JSALT workshops), and produced hundreds of PhD alumni. Our graduates are found throughout most major information processing companies and in government related research organizations.
  
* Employer: Department of Computing Science, University of Alberta
+
The primary appointment will be in the academic department most appropriate for the candidate within the Whiting School of Engineering, such as Electrical and Computer Engineering, Computer Science or another appropriate department. Applicants for this position must have a Ph.D. in Computer Science, Electrical and Computer Engineering or a closely related field, commitment to teaching, and excellent communication skills. Familiarity with some aspect of Human Language Technology or machine learning is strongly preferred. The university has instituted a nontenure track career path for fulltime teaching faculty culminating in the rank of Teaching Professor.
* Rank or Title: Post-doctoral fellow
 
* Specialty: Information Extraction
 
* Location: Edmonton, AB, Canada
 
* Deadline: March 15 2013, but applications are accepted until positions are filled
 
* Date Posted: 26 February 2013
 
* Contact email: denilson@ualberta.ca
 
  
'''Position Description'''
+
Johns Hopkins is a private university known for its commitment to academic excellence and research. CLSP, as well as the CS and ECE departments, are part of the Whiting School of Engineering. We are located in Baltimore, MD in close proximity to Washington, DC and Philadelphia, PA. See the center webpage https://www.clsp.jhu.edu/ for additional information.
  
The Department of Computing Science at the University of Alberta is seeking applicants for post-doctoral fellows to work on a project related to information extraction. The ideal candidates are recent PhDs in Computer Science with strong background in information retrieval, linked open data, natural language processing, and information extraction from the web. Other areas where expertise is desirable include graph data management, network analysis, data analytics, and the semantic web.
+
Applicants should apply online at http://apply.interfolio.com/47959. Salary and rank will be commensurate with qualifications and experience. Applicants should submit a curriculum vitae, a teaching statement and complete contact information for at least three references.  
  
The projects will be conducted in the context of the NSERC Business Intelligence Network (http://bin.cs.utoronto.ca/), a collaborative research initiative involving several top Canadian Universities and key industrial partners IBM Canada, SAP Canada, and Palomino System Innovations Inc.  
+
Applicants should apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled. Questions should be directed to clspsearch@clsp.jhu.edu.
  
The fellows will work under the supervision of PI Denilson Barbosa, within a team of PhD and MSc students, and build on ongoing work in information extraction with applications in business and environmental data. These positions will require the development of practical prototypes and proof-of-concept systems, as well as dissemination of research results in top venues. As such, emphasis should be given on the application materials to hands-on experience with large-scale datasets.
+
Johns Hopkins University is committed to active recruitment of a diverse faculty and student body. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University’s goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant.
  
Qualified candidates must hold a PhD at the time of appointment. The stipend will be in accordance with NSERC standards (CAD$ 40,000 plus benefits), with the possibility of a 10-20% top-up depending on qualifications.
 
  
'''Application instructions '''
 
  
To apply, send an updated CV, cover letter, and the names and official contact information (university or company email and phone number) of three references to Denilson Barbosa <denilson@ualberta.ca>.
+
== Post-Doctoral Position: Law, Economics, & Data Science, ETH Zurich ==
  
Applications received by March 15, 2013 will receive full consideration, but applications will be considered until the positions are filled.
+
*Employer: Center for Law & Economics, ETH Zurich
 +
*Title: Post-Doctoral Research Fellow
 +
*Location: Zurich, Switzerland
 +
*Deadline: Application review begins Feb 1st 2018; open until filled
 +
*Date Posted: December 20, 2017
 +
*Contact: Elliott Ash ([mailto:e@elliottash.com e@elliottash.com])
  
'''Other Considerations'''
 
  
The University of Alberta, one of Canada's largest research universities is situated in Edmonton, a metropolitan area of over one million people with a vibrant research community and an excellent standard of living. The Department of Computing Science at the University of Alberta is widely recognized as a leading CS department, both within Canada and worldwide.
+
'''Description:'''  Applications are invited for postdoctoral research position in a new interdisciplinary research group at Center for Law & Economics, ETH Zurich. The research group in Law, Economics, and Data Science focuses on representing legal and political language as statistical data using tools from natural language processing, and then recovering causal relations between language and outcomes in society and the economy. The postdoc will be involved in all aspects of the research, including project planning, research design, data analysis, presentation of findings at conferences, and preparation of manuscripts for submission to leading peer-reviewed journals. The postdoc will have the opportunity to co-author papers with lab colleagues, work with an array of affiliated faculty from ETH and University of Zurich, and develop independent projects related to these research areas. Organizational and teaching duties are limited to a few hours per week. Our offices are located in downtown Zurich, and the working language is English. The appointment will be for at least one year and up to three years (contingent on satisfactory performance), with flexible starting date beginning July 2018. Salaries are internationally competitive, paid according to ETH standards (https://www.ethz.ch/en/the-eth-zurich/working-teaching-and-research/working-conditions/employment-and-salary.html).
  
All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
+
'''Qualifications:'''  Applicants should have a PhD in computer science, computational linguistics, machine learning, or a related field. Applicants should have graduate-level expertise in natural language processing and machine learning. Excellent English writing skills are essential.  
  
The University of Alberta hires on the basis of merit. We are committed to the principle of equity in employment. We welcome diversity and encourage applications from all qualified women and men, including persons with disabilities, members of visible minorities, and Aboriginal persons.
+
'''How to Apply:'''  Online application available at https://apply.refline.ch/845721/5895/index.html?cid=1&lang=en. Application review will begin on February 1, 2018 and continue until the position is filled.
  
 +
== Post-Doctoral Researcher in Computational Linguistics, University of Pennsylvania ==
  
== Research Scientist - Xerox Research Centre Europe ==
+
*Employer: Department of Computer and Information Science, University of Pennsylvania
 +
*Title: Post-Doctoral Research Fellow
 +
*Location: Philadelphia, PA
 +
*Deadline: Open until filled
 +
*Date Posted:December 17, 2017
 +
*Contact Mitch Marcus (mitch@cis.upenn.edu)
  
* Employer: Xerox Research Centre Europe (XRCE) http://www.xrce.xerox.com/
 
* Rank or Title: Research Scientist
 
* Specialty: Statistical Natural Language Processing
 
* Location: Grenoble, France
 
* Deadline: Applications accepted until position is filled
 
* Date Posted: 14 February 2013
 
* Contact email: James.Henderson@xrce.xerox.com
 
  
'''Position Description'''
+
'''Description:''' Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania. This is a full time position for 18 months, starting immediately.
  
The Parsing & Semantics research area at Xerox Research Centre Europe (XRCE) is currently looking for an experienced researcher in statistical natural language processing (NLP), with a deep understanding of machine learning and/or information extraction (e.g. event extraction).  The ideal candidate would also have experience or knowledge of textual entailment, knowledge representation, and combining machine learning with expert knowledge.  The applicant should have good coding skills (e.g. Java programming), with the ability to develop research prototypes and pilots.
+
The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora. The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years. Our project is also inspired by the current understanding of how children acquire their native language, in an unsupervised setting and with relatively small amount of data. We intend to shamelessly exploit them all.  
  
The successful candidate will be expected to identify challenging problems, develop new solutions, and work with business and development teams to ensure that these solutions have a significant impact. We work together with top academic partners and expect our researchers to publish results in top-tier conferences and journals. We also have multiple open innovation collaborations with academic partners world-wide.  
+
The candidate will work under the supervision of Profs. Mitch Marcus and Lyle Ungar in Computer and Information Science and Prof. Charles Yang in Linguistics.  
  
The Parsing & Semantics group concentrates on automatically making sense of electronic documents using semantic analysis. The group focuses on natural language processing methods for robust parsing, semantic analysis, and information discovery, including the role of context in determining meaning. We are particularly interested in theoretical models of communication, language, computation, learning and inference which take into account the context in which these activities occur. The Parsing & Semantics group collaborates closely with the Machine Learning for Services group and the Machine Learning for Document Access and Translation group. We are also interested in applying research results to practical applications and real-world problems.  Our general application focus is on converting unstructured text into structured information. The solutions we develop are expected to play a key role in Xerox’ next generation document and business process outsourcing services in domains such as customer care, healthcare, and financial services.  
+
'''Qualifications:'''  The candidate should have a very strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science with a good publication record. Experience in machine learning, good programming skills, and a good knowledge of modern linguistics are required.  
  
See also http://www.xrce.xerox.com/About-XRCE/Career-opportunities
+
'''How to Apply:'''  Please email your CV and the names and contact information of three or more references to Mitch Marcus at the email provided below.
 
 
'''Requirements'''  
 
 
 
  * PhD in Computer Science or Computational Linguistics
 
* NLP knowledge and experience
 
* Knowledge or experience in machine learning or information extraction
 
* Object oriented programming skills (e.g. java)
 
* Strong written and oral communications skills in English
 
 
 
'''Application instructions '''
 
 
 
The application deadline is '''March 1, 2013''', but applications will be considered beyond this date until the position is filled.
 
 
 
Informal inquiries can be made to James.Henderson@xrce.xerox.com or Tonya.Love@xerox.com.
 
To submit an application, please send your CV and cover letter to both xrce-candidates@xrce.xerox.com and to Tonya.Love@xerox.com. You should also include in your CV at least three referees we can contact for letters of recommendation.
 
 
 
 
 
== 15 Research Positions (MT, Parsing, IR/E, Text Analytics, NLP) at CNGL at DCU ==
 
 
 
* Employer: CNGL, Dublin City University http://www.cngl.ie
 
* Rank or Title: PhD, Post-Doc and Research Programmer
 
* Specialty:  Machine Translation, Natural Language Processing, Parsing, Information Retrieval/Extraction, Text Analytics
 
* Location: Dublin, Ireland
 
* Deadline: February 25, 2013
 
* Date Posted: January 30, 2013
 
* Start Date: March, 2013
 
* Duration: 3 year (PhD), up to 2.5 years (Post-Doc)
 
* Contact email: dgroves@computing.dcu.ie
 
 
 
'''For More Details'''
 
 
 
http://www.cngl.ie/vacancies.html
 
 
 
'''Position Description'''
 
 
 
CNGL is a €50M+ Academia-Industry partnership, funded jointly by Science Foundation Ireland (SFI) and our industry partners, and is entering its second cycle of funding. CNGL is looking to fill multiple posts associated with its second phase which will focus on expansion of our work into the challenging areas of social text sources and multimedia content.
 
 
 
CNGL is an active collaboration between researchers at Dublin City University (DCU), Trinity College Dublin (TCD), University College Dublin (UCD), University of Limerick (UL), as well as 10 industrial partners, including SMEs, Microsoft, Symantec, Intel, DNP, and Welocalize.
 
 
 
CNGL comprises over 100 researchers across the various institutions developing novel technologies addressing key challenges in the global digital content and services supply chain. CNGL is involved in a large number of European FP7 projects, as well as commercial projects in the areas of language technologies, information retrieval and digital content management. CNGL provides a world class collaborative research infrastructure, including excellent computing facilities, and administrative, management and fully integrated and dedicated on-site commercialisation support.
 
 
 
The successful candidates will become part of the research team based at DCU, joining two leading academic MT/NLP/IR and Translation research groups (www.nclt.dcu.ie/, cttsdcu.wordpress.com/). The team’s location at DCU, minutes from Dublin city centre, offers a highly conducive environment for research, collaboration and innovation with a wealth of amenities on campus.
 
 
 
DCU is ranked in the TOP 50 of young universities worldwide (under 50 years old) (QS Ranking) and in the TOP 100 under the Times Higher Education (under 50 years) ranking scheme.
 
 
 
The research is supervised by Dr. Jennifer Foster, Dr. Sharon O'Brien, Dr. Gareth Jones, Prof. Qun Liu and Prof. Josef van Genabith.
 
 
 
'''PhD Studentships'''
 
 
 
*Parsing, Analytics and Information Extraction:
 
**Tuning Text Analytics to User-Generated Content: Parse quality estimation and targeted self-training.
 
**Extracting Events and Opinions from User-Generated Content: Deep parsing-based methods.
 
*Information Retrieval:
 
**Self-Managing Information Retrieval Technologies: Query, search technique and parameter selection in information retrieval applications
 
**Indexing and Search for Multimodal (Spoken/Visual) Content: Locating relevant content in multimodal sources
 
**Application of Text Analytics in Information Retrieval: Enhancing information retrieval using features from text analysis
 
**Investigating Human-Computer Interaction Issues for Search and Discovery with Multimodal (spoken/Visual) Content
 
*Machine Translation:
 
**Syntax- and Semantics-Enhanced Machine Learning Based MT
 
**Domain Adaptation Based on Multi-Dimensional Quality Estimation, Similarity Metrics, Clustering and Search
 
**Human interaction with MT output: Usability, Acceptability, Post-editing Research
 
**MT and Multimodal Interaction
 
**MT for Multimodal Cross Language Information Retrieval
 
 
 
'''Post-Doctoral Positions'''
 
 
 
*Parsing, Analytics and Information Extraction:
 
**Extracting Events and Opinions from User-Generated Content: Parsing-based deep methods (up to 2 year contract)
 
**Extracting Events and Opinions from UGC: Shallow methods, including unsupervised methods (up to 2.5 year contract)
 
*Machine Translation:
 
**User/Human Centric MT (up to 2.5 year contract)
 
 
 
'''Post-Doctoral Positions'''
 
 
 
*Research Programmer (up to 2.5 year contract)
 
 
 
For more information please see: http://www.cngl.ie/vacancies.html
 
 
 
 
 
== Assistant Professor Position in Computational Linguistics in NAIST (Nara, Japan) ==
 
 
 
* Employer: Nara Insititute of Science and Technology
 
http://www.naist.jp/en/
 
* Rank or Title: Assistant Professor
 
* Specialty:  Foundation and/or Application areas of Natural Language Processing, Machine Translation, Web Mining and Grammatical Error Correction/Detection
 
* Location: Nara, Japan
 
* Deadline: February 28, 2013
 
* Date Posted: January 30, 2013
 
* Start Date: after April, 2013
 
* Duration: 5 years (reappointment is possible)
 
* Contact email: matsu@is.naist.jp
 
 
 
'''For Detailed Description'''
 
 
 
http://www.naist.jp/en/about_naist/job_opportunities/academic_positions/index_130129.html
 
 
 
 
 
==Researchers - AT&T Labs Research==
 
 
 
* Employer: AT&T Labs - Research
 
* Rank or Title: Researchers and Research Software Engineers
 
* Specialty: Natural Language Processing, Speech Processing, Machine Learning
 
* Location: NJ
 
* Deadline: Applications accepted until position is filled
 
* Date Posted: 8 January 2013
 
* Contact email: vkumar@research.att.com
 
 
 
'''Position Description'''
 
 
 
AT&T Research, one of the premier industrial research laboratories in the world, is looking for
 
talented individuals to make a difference in the world of communications.  Our researchers and
 
research software engineers are dedicated to solving real problems in speech and language
 
processing, and are involved in inventing, creating and deploying innovative services. We also
 
explore fundamental research problems in these areas. Outstanding Ph.D.-level candidates at
 
all levels of experience are encouraged to apply.  Candidates must demonstrate excellence in
 
research, a collaborative spirit and strong communication and software skills.
 
 
 
Areas of particular interest are
 
 
 
    * Large-vocabulary automatic speech recognition
 
    * Acoustic and language modeling
 
    * Robust speech recognition
 
    * Signal processing
 
    * Text-to-speech synthesis
 
    * Natural language understanding and dialog
 
    * Machine translation (speech and text)
 
    * Speaker biometrics
 
    * Voice and multimodal search
 
    * Software engineering for speech and language processing
 
 
 
Speech and language positions are based in Bedminster, NJ; New York, NY and Middletown, NJ (note: we are moving from our Florham Park office).
 
 
 
Outstanding PhD-level candidates at all levels of experience and experienced M.S. candidates
 
are encouraged to apply.  Interviews will be conducted in early 2013.  For more information,
 
visit http://www.research.att.com/ and click on "Working with us", or access the page directly:
 
 
 
http://www.research.att.com/evergreen/working_with_us/careers.html
 
 
 
Candidates must demonstrate a proven research track record and the ability to identify technical
 
problems and research opportunities. Candidates with strong analytical and programming skills (Python, C, C++)
 
are desired. Access to massive amounts of real-world data, the ability to work with internal and external
 
collaborators across departments, the possibility of making an impact by developing solutions that will be used
 
by millions, and the freedom to publish your results are some of the reasons AT&T Labs -
 
Research is an exciting place to work.
 
 
 
AT&T Companies are Equal Opportunity Employers. Applications will continue to be considered until positions are filled.
 

Latest revision as of 15:14, 21 January 2018

PhD-level Researchers, AIPHES, Darmstadt/Heidelberg

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

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

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

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

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

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


Prerequisites

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

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

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

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

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


Associate Research Scientist, UKP Lab, TU Darmstadt

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

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

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

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

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

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

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

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

3-year research postdoc position in computational social science at Bocconi University, Milan

  • Employer: Bocconi University, marketing department, supervisor Dirk Hovy
  • Title: Postdoc
  • Specialty: NLP, neural networks, computational social science
  • Location: Milan, Italy
  • Starting date: March 1, 2018
  • Deadline: Apply by noon January 22, 2018
  • Date Posted: December 29, 2017
  • Contact: dip.mkt@unibocconi.it

Project Title: Neural methods for text analysis in the social sciences

Project Description: Text is a common medium in all social sciences, offering insights into human behavior. However, text is complex and encodes many different aspects at the same time. In order to analyze text for social science projects, we need to develop the right tools, based on natural language processing. These tools needs to scale to large amounts of text, allow for exploration and predictive modeling, and allow a multitude of analyses (classification, regression, clustering, etc). Neural-network approaches to NLP have lately demonstrated all of these properties, but have rarely been applied to social science problems. The goal of this project is to establish a baseline in tools and techniques that can be widely applied, and that can form the basis of future research and training. The full description of the position and the application details can be found at: https://www.unibocconi.eu/wps/wcm/connect/d61571c4-b0cf-4aad-a25c-b963801595bf/Call-ADR-09H1-MKT.pdf?MOD=AJPERES&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An

Responsibilities: The candidate would work predominantly on research, i.e., the implementation and testing of model architectures, data mining and preparation, and dissemination of results. Teaching opportunities (for additional salary) are available.

Scientific sector: 09/H1 Information processing systems



Teaching Faculty in Human Language Technology: Johns Hopkins University

  • Employer: Johns Hopkins University
  • Title: Senior Lecturer, Associate Teaching Professor or Teaching Professor
  • Location: Baltimore, MD
  • Deadline: Apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled
  • Date Posted: December 21, 2017
  • Contact: clspsearch@clsp.jhu.edu

The Center for Language and Speech Processing (CLSP) at Johns Hopkins University seeks outstanding candidates for a fulltime teaching position. The search is open to all ranks, including Senior Lecturer, Associate Teaching Professor and Teaching Professor.

This position will be central to CLSP’s new Certificate in Human Language Technology, part of the master’s degree programs in Computer Science (CS) and the Electrical and Computer Engineering (ECE). The successful candidate will be involved in new course development, graduate teaching, graduate academic advising, supervising master's thesis projects, and managing various aspects of the Certificate program. Although this is primarily a teaching position, there is also potential for research effort.

Successful candidates will join the faculty of CLSP, one of the largest and most visible academic organizations in speech processing and NLP. For more than two decades, CLSP has advanced the state of the art in research, hosted international research teams (the annual JSALT workshops), and produced hundreds of PhD alumni. Our graduates are found throughout most major information processing companies and in government related research organizations.

The primary appointment will be in the academic department most appropriate for the candidate within the Whiting School of Engineering, such as Electrical and Computer Engineering, Computer Science or another appropriate department. Applicants for this position must have a Ph.D. in Computer Science, Electrical and Computer Engineering or a closely related field, commitment to teaching, and excellent communication skills. Familiarity with some aspect of Human Language Technology or machine learning is strongly preferred. The university has instituted a nontenure track career path for fulltime teaching faculty culminating in the rank of Teaching Professor.

Johns Hopkins is a private university known for its commitment to academic excellence and research. CLSP, as well as the CS and ECE departments, are part of the Whiting School of Engineering. We are located in Baltimore, MD in close proximity to Washington, DC and Philadelphia, PA. See the center webpage https://www.clsp.jhu.edu/ for additional information.

Applicants should apply online at http://apply.interfolio.com/47959. Salary and rank will be commensurate with qualifications and experience. Applicants should submit a curriculum vitae, a teaching statement and complete contact information for at least three references.

Applicants should apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled. Questions should be directed to clspsearch@clsp.jhu.edu.

Johns Hopkins University is committed to active recruitment of a diverse faculty and student body. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University’s goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant.


Post-Doctoral Position: Law, Economics, & Data Science, ETH Zurich

  • Employer: Center for Law & Economics, ETH Zurich
  • Title: Post-Doctoral Research Fellow
  • Location: Zurich, Switzerland
  • Deadline: Application review begins Feb 1st 2018; open until filled
  • Date Posted: December 20, 2017
  • Contact: Elliott Ash (e@elliottash.com)


Description: Applications are invited for postdoctoral research position in a new interdisciplinary research group at Center for Law & Economics, ETH Zurich. The research group in Law, Economics, and Data Science focuses on representing legal and political language as statistical data using tools from natural language processing, and then recovering causal relations between language and outcomes in society and the economy. The postdoc will be involved in all aspects of the research, including project planning, research design, data analysis, presentation of findings at conferences, and preparation of manuscripts for submission to leading peer-reviewed journals. The postdoc will have the opportunity to co-author papers with lab colleagues, work with an array of affiliated faculty from ETH and University of Zurich, and develop independent projects related to these research areas. Organizational and teaching duties are limited to a few hours per week. Our offices are located in downtown Zurich, and the working language is English. The appointment will be for at least one year and up to three years (contingent on satisfactory performance), with flexible starting date beginning July 2018. Salaries are internationally competitive, paid according to ETH standards (https://www.ethz.ch/en/the-eth-zurich/working-teaching-and-research/working-conditions/employment-and-salary.html).

Qualifications: Applicants should have a PhD in computer science, computational linguistics, machine learning, or a related field. Applicants should have graduate-level expertise in natural language processing and machine learning. Excellent English writing skills are essential.

How to Apply: Online application available at https://apply.refline.ch/845721/5895/index.html?cid=1&lang=en. Application review will begin on February 1, 2018 and continue until the position is filled.

Post-Doctoral Researcher in Computational Linguistics, University of Pennsylvania

  • Employer: Department of Computer and Information Science, University of Pennsylvania
  • Title: Post-Doctoral Research Fellow
  • Location: Philadelphia, PA
  • Deadline: Open until filled
  • Date Posted:December 17, 2017
  • Contact Mitch Marcus (mitch@cis.upenn.edu)


Description: Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania. This is a full time position for 18 months, starting immediately.

The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora. The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years. Our project is also inspired by the current understanding of how children acquire their native language, in an unsupervised setting and with relatively small amount of data. We intend to shamelessly exploit them all.

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

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

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