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thesis, previous experience with neuroimaging, numerical mathematics, optimization, inverse problems, software development, motivation and research interests. The location for this research will be
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or computational science Strong mathematical skills and interest in developing new mathematical methods Good knowledge of mathematical/numerical optimization methods or deep learning methods Enthusiasm
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assessment, you will develop new, sample-efficient optimal control approaches for gate calibration and test them in numerical simulations. You will pursue your research with the German research collaboration
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knowledge of energy system modelling or climate modelling Good knowledge of deep learning, PDEs or mathematical/numerical optimization methods Enthusiasm for challenging problems and interdisciplinary
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linkages based on numerical simulations and to transform them into AI- and ML-ready information to develop and implement an indirect inverse optimization framework to identify microstructures that exhibit
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the Research Group “Nonlinear Optimization and Inverse Problems” (Head: Prof. Dr. D. Hömberg) starting as soon as possible. The project is part of a BMBF project concerning industrial scale data preparation
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Your Job: develop numerical and analytical techniques to simulate and control the time dynamics of quantum technology devices implement and optimize gate operations and artificial Hamiltonians
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Superconductors" at the Institute of Metallic Materials (IMW) offers a PhD position (m/f/div) in the field of superconducting dynamos Main tasks: The central research task is to investigate and optimize the use
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transmission. The successful candidate will work on elucidating the regulation of these channels and developing and optimizing gene therapeutic approaches in mouse disease models to prepare for putative future
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doctoral schools in the natural sciences and one in the humanities and social sciences as well as numerous smaller research training groups. Advising The consulting team of the Graduate Academy’s Service