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into mobility and energy systems. We improve the efficiency, sustainability and economics of electric vehicles by optimizing and accelerating the integration of components up to complex mobility systems through
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conducted in collaboration with partners in Europe, the Argentinean National Research Council (CONICET) and the International Livestock Research Institute (ILRI), based in Kenya and their network of research
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Europe, the Argentinean National Research Council (CONICET) and the International Livestock Research Institute (ILRI), based in Kenya and their network of research partners. Your tasks will be to design
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algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems coordinate distributed
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networks. These systems will have tunable chemical and photophysical properties for the translational development of platform technologies in the advanced materials sciences. This is a highly
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networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning for inverse
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scientists of the Futurelab offers an outstanding opportunity for networking and the development of followup projects. The position will be remunerated between W1 and W3 equivalent according to your
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complex multiphysics problems. The coupling is done across package boundaries. This also requires more sophisticated approaches in load-balancing. Finally, the newly developed algorithms will be tested and