LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN (LMU)
Machine learning, dynamical systems, and control: Fully funded PhD positions in
LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN (LMU), Germantown, Ohio, United States
LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN (LMU)
Organisation/Company LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN (LMU) Research Field Computer science Mathematics Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Germany Application Deadline 13 Nov 2025 - 23:59 (Europe/Berlin) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Apr 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
The Research Training Group "Machine Learning and Control Theory: Exploring Synergies, Complementarities and Mutual Benefits" (METEOR) is offering 10 PhD positions ranked according to the German TV-L E13 scale (100%), for periods of four years, starting in April 2026. METEOR is a joint initiative between the University of Munich (LMU) and the Technical University of Munich (TUM) funded by the German Research Foundation (DFG). It aims to train a new generation of researchers specializing in the intersection of machine learning and control theory for complex dynamical systems. The RTG will pursue four main research themes: Modeling and Quantification of Uncertainty for Robust Control Representation for Dynamical Systems and Control Control Theory for Machine Learning Algorithm Design Formal Analysis of Machine Learning Algorithms via Control Theory
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The Research Training Group "Machine Learning and Control Theory: Exploring Synergies, Complementarities and Mutual Benefits" (METEOR) is offering 10 PhD positions ranked according to the German TV-L E13 scale (100%), for periods of four years, starting in April 2026. METEOR is a joint initiative between the University of Munich (LMU) and the Technical University of Munich (TUM) funded by the German Research Foundation (DFG). It aims to train a new generation of researchers specializing in the intersection of machine learning and control theory for complex dynamical systems. The RTG will pursue four main research themes: Modeling and Quantification of Uncertainty for Robust Control Representation for Dynamical Systems and Control Control Theory for Machine Learning Algorithm Design Formal Analysis of Machine Learning Algorithms via Control Theory
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