We invite applications for one PhD student position in natural language generation or summarization. The goal of this position is to develop a system for text generation that is tailored at the discourse level to the user (in terms of e.g., verbosity of what is explained, vocabulary usage, explicitness of coherence relations). To this end, the generation system will model language understanding in the human user, and tailor its production accordingly.
The position, to be established in thegroup "Computer Science and Computational Linguistics" (Prof. Vera Demberg) <https://www.uni-saarland.de/lehrstuhl/demberg.html>, is part of the newly funded ERC Starting Grant project"Individualized Interaction in Discourse" (IDDISC) <https://www.uni-saarland.de/lehrstuhl/demberg/individualized-interaction-in-discourse-iddisc.html>. Project IDDISC aims at more adaptive language interaction at the discourse level, including personalized summaries or instructions. There will also be the opportunity to closely collaborate with researchers working on the DFG-fundedCollaborative Research Center on Information Density and Linguistic Encoding <http://www.sfb1102.uni-saarland.de/>(SFB 1102) <http://www.sfb1102.uni-saarland.de/>.
Candidates for this position should have a master's degree in computational linguistics, computer science or a related discipline. Experience with machine learning including deep learning is expected. The research will be conducted in English.
Dates: *application deadline: April 30, 2022*
start date: autumn 2022
The expected duration of the PhD is 3.5 years, the position is paid according to 75% TV-L E13, see alsohttps://oeffentlicher-dienst.info/c/t/rechner/tv-l/west?id=tv-l-2020&matrix=12 <https://oeffentlicher-dienst.info/c/t/rechner/tv-l/west?id=tv-l-2020&matrix=12>.
The job does not come with any teaching obligation. You can however choose to participate in teaching activities (tutoring or co-teaching).
Applicants are requested to submit their application, including a cover letter that specifies why you would like to work on this topic and what qualifies you for it, an academic CV, a list of academic publications, your MSc thesis (or a current draft), copies of academic degree certificates and names of two potential references. Please also include a 2-page research proposal in your application which outlines how you would approach the topic (choose one topic among multitask learning, domain adaptation or connective generation for discourse coherence).
Saarland University <https://www.uni-saarland.de/en/home.html> is one of the leading centres for computational linguistics and computer science in Europe, and offers a dynamic and stimulating research environment. It is famous for its interdisciplinary research in language, translation, computation and cognition. The group is affiliated with both theDepartment of Computer Science <https://www.uni-saarland.de/fachrichtung/informatik.html>and with the Department of Language Science and Technology <https://www.lst.uni-saarland.de/>. The Department of Language Science and Technology organizes about 100 research staff in ten research groups in the fields of computational linguistics, psycholinguistics, speech processing, and corpus linguistics.
Both departments are part of the Saarland Informatics Campus <https://saarland-informatics-campus.de/en>, which brings together 800 researchers and 2000 students from 81 countries. We collaborate closely with the university's Department of Computer Science, the Max Planck Institute for Informatics <https://www.mpi-inf.mpg.de/home/>, the Max Planck Institute for Software Systems <https://www.mpi-sws.org/>, and the German Research Center for Artificial Intelligence <https://www.dfki.de/en/web/> (DFKI).
Our researchers and students come from all over the world, and our primary working language is English.
Saarland University is an equal opportunity employer. Applications of women are strongly encouraged; applications of disabled persons will be given preferential treatment to those of other candidates with equal qualifications.
Applications should be sent via email directly to Prof. Vera Demberg (vera(at)coli.uni-saarland.de), quoting opening number 2079.
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