47 parallel-computing-numerical-methods PhD scholarships at Technical University of Munich
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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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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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policy, economic sociology, and international relations. Methodologically, it draws on and combines both quantitative and qualitative methods, with a particular focus on computational and multi-method
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, our group is actively involved in the Research Training Group "Targets in Toxicology", a structured Ph.D. program that unites 13 research partners in Munich, including LMU Munich, Helmholtz Zentrum
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31.01.2025, Wissenschaftliches Personal We have two open PhD positions funded by the Marie Skłodowska-Curie Actions (MSCA), the European Union’s flagship program for doctoral education. About us
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failure mechanisms. The performance of the developed methods will be evaluated using real operating data. In addition, it will be investigated how reliability and safety conditions can be taken into account
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from
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of experimental & numerical research on reversible high-temperature heat pump technologies for medium & deep geothermal energy. Your tasks: You will investigate and optimise two of our reversible high-temperature
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and industry insights. The candidate will be expected to: Apply advanced analytical and AI methods to solve real-world operational challenges. Publish in leading journals and present research
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the future of healthcare, science, technology, society, and the environment. Our mission encompasses both theoretical and empirical methods to foster ethical, transparent, and interdisciplinary research