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Your Job: Digital methods for inverse materials design are essential to efficiently create new, sustainable and recycling-adapted structural metals. Alloys with a reduced number of elements, so
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Some experience with numerical simulations such as the Finite Element Method (FEM) and Multi-Body Simulation (MBS) is a plus. We offer: a fascinating understanding at mobility in general with a
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, either in social anthropology, science and technology studies (STS), sociology or a closely related discipline (required) experience with qualitative ethnographic methods (required) proficiency in written
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computing Advanced knowledge of numerical methods Geophysical fieldwork experience, preferably with GPR, EMI and ERT Strong English writing skills Since the work involves interdisciplinary cooperation with
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on methods development in machine learning, uncertainty quantification and high performance computing with context of applications from the natural sciences, engineering and beyond. It is embedded in
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-field measurements, HPC-based numerical simulations, and laboratory experiments. Oldenburg is particularly renowned for its unique large wind tunnel with an active grid and leading expertise in developing
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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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interest in developing theoretical models and methods as well as in implementing numerical optimization techniques Interest in working closely with experimentalists Detailed knowledge of quantum physics and
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(university diploma or master's degree) in the field of geosciences, engineering or physics. Ideally, you have knowledge of numerical methods and experience with common programming languages (e.g. Matlab