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University of Munich (TUM). Please view our privacy policy on collecting and processing personal data in the course of the application process pursuant to Art. 13 of the General Data Protection Regulation
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to 2 years; an extension of an additional 2 years is possible. TASKS: Mathematical and physical modeling to determine greenhouse gas and pollutant emissions in cities using novel atmospheric measurements
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energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes
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24.02.2022, Wissenschaftliches Personal The Munich Quantum Valley aims at developing a full quantum computing stack, from the application level to the physical quantum hardware. Within
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pollution, an existential threat to Europe and the world, impacts the safety, comfort and health of humans and vegetation. It is the largest environmental cause of multiple mental and physical diseases and of
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application to the European mission of a Digital Twin Earth. ML research directions will include physics-aware machine learning, reasoning, uncertainty estimation, Explainable AI, Sparse Labels and
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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
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. Your qualifications ▪ Above-average university degree in electrical engineering, communications engineering, mathematics, physics (or similar) with thorough knowledge in quantum information and
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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
-robot-teams, haptic assistance, cyber-physical systems, and infrastructure systems. While our core competence is control engineering, we have some interdisciplinary collaborations with the fields