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efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation
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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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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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. 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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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
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for quantum computers and develop methods and software tools dedicated to the design and realization of quantum algorithms/circuits. We see ourselves as an interface between the stakeholders building physical
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companies from all over the world, especially the USA, the UK, and Germany. Your Profile: - Ph.D. in chemistry, material science, engineering, physics, or a closely-related field - Knowledge in material