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Technical University of Munich

PhD/ Post-Doc - Intersections of Control Theory and Machine Learning @ METEOR

ITR is part of the DFG Research and Training Group METEOR and will host PhDs and Post-Docs.

The core objective of this RTG is to bridge the gap between control theory (CT) and machine learning (ML) and to train a new generation of scientists with skills on both sides. Such scientists are urgently needed to face the challenges of modern artificial intelligence (AI) research and to establish datadriven discovery as the “fourth paradigm” of scientific discovery.

Applications are currently open unitl 13.11.2025 through the programs portal.

Excellent applicants have a strong disciplinary background, are enthusiastic, creative, and eager to work independently within an interdisciplinary environment. The position is remunerated at pay grade E13 TV-L.

About us:

At the Chair of Information-Oriented Control we focus on research and teaching of control and optimization of cooperative, networked, and distributed dynamical systems. We develop novel methods and tools for the analysis and control of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human-robot-teams, haptic assistance, cyber-physical systems, and infrastructure systems. While our core competence is control engineering and robotics, we have some interdisciplinary collaborations with the fields of psychology (in human-robot interaction) and communications (in networked control systems). Many of the developed methods are experimentally validated in our multi-robot lab.

To learn more about our research and ongoing projects, we invite you to read our current publications and visit the websites of our individual team members. If you have questions about our group culture or specific research topics, please feel free to contact us. However, make sure to first check the FAQs to see if your question has already been answered.

Your profil:

  • Completed university degree in engineering, computer science, mathematics, physics, or a comparable field.
  • Enthusiasm, creativity, and the ability to work independently and responsibly.
  • Convincing academic record.
  • Solid knowledge of control theory and machine learning, ideally also statistics and robotics.
  • Experience with higher-level programming languages such as C++, Python, MATLAB, or Julia.

We offer:

Application:

Please apply through the projects application portal https://www.portal.graduatecenter.lmu.de/ocgc/meteor. 

TUM is especially encouraging minorities and women to apply, because of its strong commitment to diversity in engineering education, research, and practice.

 

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