[DMANET] PhD position in Reinforcement Learning for Automatic Discovery of Dynamical Systems from Data

We are offering a PhD position in Applied Mathematics and Machine Learning, focused on the intersection of reinforcement learning, optimization, and dynamical systems identification. The project aims to develop reinforcement learning methods for the automatic discovery of nonlinear dynamical systems from data, combining ideas from:     reinforcement learning and sequential decision-making     system identification and inverse problems     optimization and control theory     representation learning for structured dynamical models The goal is to design algorithms that can learn governing equations or compact dynamical representations from observations, with a focus on scalability, robustness, and theoretical guarantees. Applications will be used as motivating benchmarks, but the core emphasis is methodological: building general-purpose frameworks for data-driven discovery of dynamical systems. This position is suited for candidates interested in theoretical and algorithmic aspects of modern ML, particularly those working at the interface of reinforcement learning, optimization, and mathematical modeling. Location: Montpellier, France Deadline: May 4 Applications must be submitted via the doctoral school ED I2S portal (Université de Montpellier): https://edi2s.umontpellier.fr → PhD offers → Statistics and Data Science → LPHI – Reinforcement learning for automatic model discovery Kind regards, Ovidiu Radulescu -- Prof. Ovidiu Radulescu University of Montpellier Laboratory of Pathogens and Host Immunity Leader, Computational Systems Biology team ------------------------------------------------------------------------ LPHI - UMR 5294 CNRS/UM/INSERM Phone: +33-(0)4-6714-9221 Pl. E. Bataillon - Bat. 24 Fax: +33-(0)4-6714-4286 Université de Montpellier email: ovidiu.radulescu@umontpellier.fr CP 107 34095 Montpellier Cedex 5 FRANCE ********************************************************** * * Contributions to be spread via DMANET are submitted to * * DMANET@zpr.uni-koeln.de * * Replies to a message carried on DMANET should NOT be * addressed to DMANET but to the original sender. The * original sender, however, is invited to prepare an * update of the replies received and to communicate it * via DMANET. * * DISCRETE MATHEMATICS AND ALGORITHMS NETWORK (DMANET) * http://www.zaik.uni-koeln.de/AFS/publications/dmanet/ * **********************************************************