Difference between revisions of "Employment opportunities, postdoctoral positions, summer jobs"

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Processing and Computational Linguistics
 
Processing and Computational Linguistics
  
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from  
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The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in  
Heterogeneous Sources” (AIPHES)], which has been established in  
 
 
2015 at Technische Universität Darmstadt and at Ruprecht Karls  
 
2015 at Technische Universität Darmstadt and at Ruprecht Karls  
 
University Heidelberg is filling several positions for three years,  
 
University Heidelberg is filling several positions for three years,  
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The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly  
 
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  
 
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  
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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  
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Ruprecht Karls University Heidelberg is one of the largest centers  
 
for computational linguistics both in Germany and internationally. The  
 
for computational linguistics both in Germany and internationally. The  
 
ICL and the NLP department of the HITS jointly run the graduate  
 
ICL and the NLP department of the HITS jointly run the graduate  

Revision as of 16:14, 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.