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Systems, Tübingen/Stuttgart in Germany. Together we want to build a lighthouse for machine learning and modern artificial intelligence in Europe. The cooperation spans all levels, from leading experts
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-friendly frameworks for multimodal elastography and enabling deployment on portable devices (e.g., smartphones) for real-time diagnostics. The research combines continuum mechanics, machine learning
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, non-linear contact interactions, and varying surface conditions. Reinforcement learning (RL) offers a promising approach to develop adaptive and robust control policies, but training on physical
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, organization, compression, analysis, and visualization of georeferenced or geometric data on large scales. We put emphasis on methods of distributed computing, machine learning, image and text analysis
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Do students receive financial aid? All doctoral positions are fully funded, including social benefits. Students also receive funding to attend conferences and other events related to their research, and have access to outstanding facilities. Do I need to know English? Yes, English is the...
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parameterization and shows limited adaptability to different vehicle types and operating conditions. The aim of the master's thesis is to investigate an end-to-end reinforcement learning approach for path tracking
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(Computer Science), in the research group “Computer Graphics and Virtual Reality” of Prof. Gabriel Zachmann, within the EU project SENSORAMA (Horizon Europe), we are seeking to fill the following position
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19.07.2022, Academic staff The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current focus on deep
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modeling and probabilistic machine learning, tackling problems that arise in molecular systems and heterogeneous materials. Eine Postdoktorandenstelle im Bereich physik-informiertes generatives Modellieren
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-based modeling and probabilistic machine learning, tackling problems that arise in molecular systems and heterogeneous materials. Eine Doktorandenstelle im Bereich physik-informiertes generatives