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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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:100% of the full-time weekly hours Tasks: The PhD student will be responsible for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs
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institution. The “Friedrich List" Faculty of Transport and Traffic Sciences comprises more than 20 Chairs with numerous scientists and research projects on all modes of transport and mobility needs
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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cell development and function, and compare the (epi)genetic profiles characteristic of individual genetic defects. These studies will be complemented by modeling disease mechanisms in suitable cell lines
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patterns, such as those observed in turbine wakes. The ultimate goal is to apply this enhanced model to generate numerical wind fields that will serve as inputs for the digital twin of a megastructure
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The University Medical Center Göttingen (UMG) unites the Medical Faculty of the Georg-August University and the University Hospital in an integration model. With around 9,700 employees, the UMG and
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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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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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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