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: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically mathematics, physics). For Postdoc applicants: Excellent track record in computer science
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following areas: Mathematical Analysis/ Numerical Analysis/ Theoretical Machine Learning Please note: Applications from candidates with degrees in other disciplines (e.g., Computer Science, Engineering) will
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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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science & physics, biomaterials, nanotechnology, electrical engineering, and neurobiology. To learn more about our group’s recent work in this field, please check out some of our recent publications, here
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planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
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disciplines (typically mathematics, physics). For Postdocapplicants: Excellent track recordin computer science or engineering. Fluency in spoken and written English is required. Proficient in at least one
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. The team is located within the School of Computation, Information and Technology at the Technical University of Munich, an internationally renowned university with excellent connections to leading research
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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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. 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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” at Technical University Munich in the Department of Physics. The position is part of the Focus Group Molecular and Interfacial Engineering of Organic Nanosystems at the Institute for Advanced Study (IAS) headed