49 scheduling-algorithms-"Prof" PhD positions at Technical University of Munich in Germany
Sort by
Refine Your Search
-
29.09.2022, Wissenschaftliches Personal Join the team of Prof. Karen Alim at the TUM Campus Garching to investigate how blood vessels self-organize their network to reach uniform blood flow within
-
about the positions and the application process, please contact Prof. Dr. Gjergji Kasneci (gjergji.kasneci@tum.de ). The position is suitable for disabled persons. Disabled applicants will be given
-
02.05.2022, Wissenschaftliches Personal Join the team of Prof. Karen Alim at the TUM Campus Garching to investigate how the complex organism-scale behaviour in the slime mould Physarum
-
05.04.2023, Wissenschaftliches Personal We are the Autonomous Vehicles Systems (AVS) Lab and are interested in the algorithmic foundations of path and behaviour planning, control and automated
-
05.04.2023, Wissenschaftliches Personal We are the Autonomous Vehicles Systems (AVS) Lab and are interested in the algorithmic foundations of path and behaviour planning, control and automated
-
Medicine (Director: Prof. Dr. Daniel Rueckert) is seeking to fill PhD candidate position (TV-L E13, 100% for 3 years) in Privacy-Preserving and Reliable Artificial Intelligence to be occupied starting from
-
Biotechnologie und Nachhaltigkeit Prof. Dr. Marc Ledendecker Email: marc.ledendecker@tum.de Web: www.ledendecker-research.com The position is suitable for disabled persons. Disabled applicants will be given
-
note of the data protection no-tices of TUM. Technical University of Munich Institute of Turbomachinery and Flight Propulsion, Prof. Dr.-Ing. Volker Gümmer Secretarial Office, Frau Delphine Hase
-
03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
-
03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and