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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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05.05.2025, Wissenschaftliches Personal The Chair of Human-Centered Technologies for Learning at the Technical University of Munich (TUM) offers exciting Ph.D. and PostDoc opportunities focused
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planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
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science & physics, biomaterials, nanotechnology, electrical engineering, and neurobiology. To learn more about our group’s recent work in this field, please check out some of our recent publications, here
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learning, such as the rapid generation of realistic implant geometries or the learning of biomedical parameters from experimental or clinical datasets. Specific tasks within the project include
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard
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the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We
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: - QUANTITATIVE VERIFICATION: analysis of probabilistic systems (Markov decision processes, stochastic games, chemical reaction networks), automata theory and temporal logic, machine learning in verification