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- PhD student in quantitative verification interested in co-developing Automata Tutor - main developer of Automata Tutor Positions in the Formal Methods for Software Reliability group of TU Munich led by
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vibrant and interdisciplinary research environment at TUM Access to unique datasets and collaboration with a well-established European network Opportunities for professional development and academic career
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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“NANeurO,” which focuses on the development of injectable nanoelectrodes for wireless and minimally invasive neural stimulation. About us The NEN Lab works with new materials for wireless communication with
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will join the newly established research group of Dr. Torsten V. Zache at the Technical University of Munich. Our group is broadly interested in the theoretical development and application of quantum
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smart grid). While there has been tremendous progress in formal verification of cyber-physical systems, existing approaches still require expert knowledge. The main goal of this project is to develop
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic
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. German language is not required. The successful candidate will have the opportunity to work on an exciting and diverse project within a nationwide research network, with numerous opportunities for development
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journals (e.g., ICRA, RSS, IJRR) Active participation in European robotics and AI research initiatives Support for personal and professional development, including teaching, supervision, and leadership roles
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harms, but also how these harms should be redressed through multi-sited ethnographic fieldwork. This fieldwork will be integrated with participatory design workshops to develop specific interventions