: Machine Learning for Natural Languages and other sequence data, Saarland University, Germany

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(Computer Science, Computational Linguistics, Physics  or similar)

The research group is focusing on getting a deeper understanding of how modern deep learning methods can be applied to natural languages or other sequence papers. Our recent achievements include a best paper award at COLING 2022 and a best theme paper award at ACL 2023. We offer a PhD position that is topically open and should have a strong focus on applying machine learning techniques to natural language data or other sequence data (e.g., string representations of chemical compounds).

The ideal candidate for the position would have:

   1. Excellent knowledge of machine learning and deep learning

   2. Excellent programming skills

   3. Masters degree in Computer Science, Computational Linguistics, Physics, or similar

Salary: The PhD position will be 75% of full time on the German E13 scale (TV-L) which is about 3144€ per month before tax and social security contributions. The appointments will be for three years with a possible extension at 50%.

About the department: The department of Language Science and Technology is one of the leading departments in the speech and language area in Europe. The flagship project at the moment is the CRC on Information Density and Linguistic Encoding. It also runs a significant number of European and nationally funded projects. In total, it has seven faculty and around 50 postdoctoral researchers and PhD students. The department is part of the Saarland Informatics Campus. With 900 researchers, two Max Planck institutes and the German Research Center for Artificial Intelligence, it is one of the leading locations for Informatics in Germany and Europe.

How to apply: Please send us a letter of motivation, a research plan (max one page), your CV, your transcripts, if available a list of publications, and the names and contact information of at least two references, as a single PDF or a link to a PDF if the file size is more than 5 MB.

Please apply latest by November 20th, 2023. Earlier applications are welcome and will be processed as they come in.