W3-Professorship in Machine Learning in Physics

Cyber Valley GmbH

Tübingen

Hybrid

EUR 110.000 - 150.000

Vollzeit

14 Tage+
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Zusammenfassung

The University of Tübingen invites applications for a W3-Professorship in Machine Learning in Physics in the Department of Physics, to begin as soon as possible. The appointment is embedded within the Excellence Cluster "Machine Learning: New Perspectives for Science" and aims to integrate research across physics and ML.

The successful candidate will have an established physics research profile and a strong track record in ML/AI, with teaching duties in the physics department and collaboration

Qualifikationen

  • PhD or equivalent degree required.
  • Postdoctoral qualifications and teaching experience expected for a full professorship.
  • Strong research record in ML/AI integrated with physics.

Aufgaben

  • Develop and lead research at the interface of machine learning and physics.
  • Contribute to teaching in the Department of Physics and the international ML Master program.
  • Engage in organizational tasks within the Excellence Cluster and collaborate with research centers.

Ausbildung

PhD or equivalent degree

Jobbeschreibung

W3-Professorship in Machine Learning in Physics

The Faculty of Science at Tübingen University invites applications for a W3-Professorship in Machine Learning in Physics at the Department of Physics starting as soon as possible.

The professorship is embedded within the Excellence Cluster "Machine Learning: New Perspectives for Science", which is now entering its second funding phase. The successful candidate is expected to have an established research profile in a core area of physics, as well as a strong track record in research questions related to machine learning and/or artificial intelligence.

Core areas of physics include the structure of condensed matter (description of many-body systems), quantum physics (characterization of quantum states in many-body systems), and theoretical particle physics. In all of these areas, methodological development through machine learning is taking place — for example, in predicting the evolution of complex molecular systems over long timescales, investigating quantum mechanical effects in information processing within (quantum) neural networks, or in elementary particle physics at high-energy accelerators.

The aim of the professorship is to closely integrate research at one of the Department of Physics’ research centers (BioNanoPhysics Center, Center for Quantum Science, or Kepler Center) with ongoing machine learning research activities in Tübingen. The appointee is expected to be actively involved in the Department of Physics and in the Excellence Cluster, inter alia by pursuing collaborative research projects at the interface of machine learning and physics, as well as by committing to organizational and implementation-related tasks within the Excellence Cluster. Further information about the Excellence Cluster can be found at: http://www.ml-in-science.uni-tuebingen.de/

In terms of teaching, the professorship is expected to offer courses within the Department of Physics and also contribute to the international Master's program "Machine Learning" offered by the Department of Computer Science.

Required qualifications include a PhD or equivalent degree as well as postdoctoral qualifications and teaching experience equivalent to the requirements of a full professorship.

The University of Tübingen is committed to equity and diversity and actively promotes equal opportunities. Female academics, in particular, are explicitly invited to apply, as are applicants from outside Germany. Applications from equally qualified candidates with disabilities will be given preference.

Please submit your full application through the application site of the University of Tübingen at https://berufungen.uni-tuebingen.de by 15 February 2026. Questions concerning the call for applications and the application portal can be directed to the Dean of the Faculty of Science at the University of Tübingen, Professor Dr. Thilo Stehle (career@mnf.uni-tuebingen.de ).

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