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Full Professorship in Machine Learning
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stellenwerk
Full Professorship in Machine Learning
Job summary
A prestigious research institution in Konstanz seeks a Full Professorship in Machine Learning. The position involves establishing a research group dedicated to machine learning methods and theoretical principles. Applicants should be recognized in their field and ideally pursue interdisciplinary research focused on social sciences. Ideal candidates are to submit their applications by January 31, 2026, including CV, publication list, teaching experience, and research statements.
Qualifications
- Internationally recognized in at least one current research area of machine learning.
- Engagement in interdisciplinary research with applications in social sciences.
Responsibilities
- Establish a research group focusing on methods and theoretical principles of machine learning.
The University of Konstanz is a dynamic and internationally successful research university which has been continuously funded by the German Excellence Strategy since 2006.
The Department of Computer and Information Science seeks to fill the position of a
Full Professorship (W3) in Machine Learning
The professorship is expected to establish a research group focusing on methods and theoretical principles of machine learning. Applicants should be internationally recognized in at least one current research area of machine learning and ideally engage in interdisciplinary research with applications in the social sciences.
We look forward to receiving your application with the usual documents (curriculum vitae, publication list, a list of grants and awards, details of teaching experience, statements on current research topics, future research directions and interests) until January 31, 2026 via our Online Application Portal, where further information may be found:
https://stellen.uni-konstanz.de/jobposting/6fb92b2d8de7379a32133932a66b0d6b68b911920
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.