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Design and implement optimization techniques for full-stack improvement of quantum algorithms Model major sources of experimental error for control theory or for error mitigation techniques Scientific
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, ACL, ICLR, EMNLP, NAACL or COLM); Have excellent programming skills; Have strong mathematical skills (e.g., probability theory, statistics, calculus, and linear algebra); Have strong communication
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Requirements a Ph.D. degree in Physics or a related discipline Strong background in one or more of the following areas: integrated photonics, 2D materials, topological physics (theory), nanofabrication
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conventional methods. By combining advanced experiments with collaborations in theory and modeling, our research aims not only to deepen the fundamental understanding of ferroic systems, but also to open new
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Learning Formal Methods Dynamical Systems Control Theory Context The applicant will be directly advised by Prof. Matthias Althoff (https://www.ce.cit.tum.de/cps/members/prof-dr-ing-matthias-althoff
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molecules · Quantum many-body physics with ultracold polar molecules · Controlling collisions between laser-cooled molecules and atoms The grants are in collaboration with the experimental groups
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for model calibration and validation. Develop models - potentially adopting first principles theories, coarse computational description and/or machine learning / artificial intelligence methods – to describe
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power grids. In this role, you will combine theory and experimentation to address one of the most critical challenges in modern energy systems, maintaining stability in an increasingly converter-dominated
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(geophysics, physics, biology, mechanics, and computer science), to other areas of mathematics (e.g., geometry applied to control theory), or to pedagogy. Recurrent algal and/or cyanobacterial blooms constitute
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We are looking for a postdoctoral researcher who wants to contribute to the development of next-generation frameworks for resilient power grids. In this role, you will combine theory and