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knowledge of energy system modelling or climate modelling Good knowledge of PDEs or mathematical/numerical optimization methods Enthusiasm for challenging problems and interdisciplinary collaboration Relevant
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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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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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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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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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methods as well as in implementing numerical optimization techniques Interest in working closely with experimentalists Detailed knowledge of quantum physics and experience with quantum technology Strong
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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
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Description A PhD position is available at the Chair for Combinatorial Optimization headed by Prof. Nicole Megow (https://www.uni-bremen.de/en/cslog/nmegow) at the University of Bremen. The research
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optimal conditions for their successful doctoral degree and beyond. Doctoral researchers at GS SimTech: have at least two supervisors from different subject areas benefit from a second, external reviewer