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Open Position (PhD student or postdoc level): Structured Multi-Domain Emotion Analysis from Text

15. September 2017; Roman Klinger

The research group for Information Extraction and Interpretation
(headed by Roman Klinger, part of the chair for theoretical
computational linguistics at the Institute for Natural Language
Processing at University of Stuttgart) has an opening for a researcher
to work in emotion recognition in natural language.

The position is available in the context of the project SEAT,
funded by the German Research Council (DFG).
The successful candidate will develop methods to identify emotion
mentions in the context of modifiers as well as associated roles
(experiencer/feeler, cause, target, theme) in different domains,
for instance literature, news and social media.

The candidate has the chance to collaborate with the DFG project “ Comprehensive Modeling of Conversational Contributions in Prose Texts” and the Center for Reflected Text Analytics (CRETA), in which a subproject already works on emotion recognition for literary studies.

We invite applications for this position both on PhD student and Postdoc level.

The candidate for the position should have the following qualifications:

  • excellent Master’s degree in computer science, computational linguistics or similar
  • advanced knowledge of machine learning methods, for instance for multi-task or joint learning with probabilistic graphical models or neural networks
  • strong programming skills in object-oriented and scripting languages
  • advanced knowledge of natural language processing
  • excellent communication skills and interest in interdisciplinary work

 The following skills will be considered as a plus:

  • Previous experience with sentiment analysis, affective computing or emotion analysis
  • Knowledge of transfer learning, domain adaptation, active learning, or reinforcement learning
  • Knowledge of distributional semantics
  • Knowledge of the German language

The position will be available for three years, starting in Fall 2017 or Winter 2017/2018 and open until filled. All applications received until 15th of October 2017 will receive full consideration. The salary is according to the German university payscale (TV-L 13, between 66% and 100% for Ph.D. student depending on qualifications, 100% for Postdoc, see e.g. here for details.

To apply, please send a full CV and letter of motivation in one (1!) PDF document to Roman Klinger (klinger@ims.uni-stuttgart.de).

 

About Stuttgart and the University of Stuttgart:
The University of Stuttgart is a technically oriented university in Germany of long standing. It is especially known for engineering and related topics, with its computer science department being ranked highly nationally and internationally. The Institute of Natural Language Processing (Institut für Maschinelle Sprachverarbeitung, IMS), which forms part of the Faculty of Computer Science and Electrical Engineering, is one of the largest academic research institutes for natural language processing in Germany, with three full professors, an assistant professor, three senior lecturers and a staff of more than thirty researchers. Its activities range from computational corpus linguistics to semantic processing, machine translation, psycholinguistics, and phonetics, and hosts several projects funded by the EC, the German science council (DFG), and various foundations. The institute manages dedicated BSc and MSc programs in computational linguistics.

The city of Stuttgart [4] is the capital of the state of Baden-Württemberg in the south-west of Germany and known for its strong economy, rich culture and its location across a variety of hills, many covered in vineyards. It is a lively place with an active bar and club scene. With Germany’s high-speed train system, it is well-connected to many other interesting places, for instance Munich and Cologne (~2.5 hours), Paris (~3.25 hours), Berlin (5.5 ~hours), Strasbourg (<1.5 hours) or Lake Constance (~2.5 hours).

  

[1] http://www.romanklinger.de/
[2] http://www.ims.uni-stuttgart.de/institut/arbeitsgruppen/tcl
[3] http://oeffentlicher-dienst.info/c/t/rechner/tv-l/west?id=tv-l&g=E_13
[4] https://www.stuttgart-tourist.de/en