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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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near-real-time forecast system for the Baltic Sea Generate high-resolution daily surface salinity maps for the Baltic Sea and validate them with available observational datasets Develop algorithms and
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algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website: https://www.math.cit.tum.de/en/math/home/. The position is a full-time position (100%), initially
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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication
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) Participation in international conferences (including presenting your research results) Preparation of scientific publications and project reports Supervision of PhD students and other students Support in
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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project team on “Participatory Algorithmic Justice: A multi-sited ethnography to advance algorithmic justice through participatory design” (PARTIALJUSTICE) to examine issues of justice and participation in
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: Masters and subsequent PhD in Physics, Chemistry, Material Science or related disciplines Experience in neutron spectroscopy, e.g. INS, QENS, NSE Good knowledge of the structural characterization of matter
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activities. Your Profile: Master and PhD degree in astronomy, physics, computer science or equivalent fields of study. Proven experience in N-body simulations and the comparison of simulation and observation
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reports Develop and apply software tools Document software and data according to the FAIR data principles Contribute to workshops and training activities Your Profile: Master with subsequent PhD degree in