163 parallel-computing-numerical-methods positions at Technical University of Munich in Germany
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investigations carried out on the research compressor by an integrated team of LTF and an industry partner. - Numerical modelling compressor stages and carry out simulation of methods to enhance aerodynamic
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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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computer vision in dusty conditions by incorporating hyperspectral cameras. In addition, assisting in project applications and general development duties of the Chair. The position is available 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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talented individuals passionate about AI, Human-Computer Interaction, Eye-Tracking, and their responsible applications. Ideal candidates will have: • An M.Sc. degree (or equivalent) in Computer Science, Game
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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
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• Conduct statistical consultation for Helmholtz scientists and industry partners • Evaluate and apply novel statistical methods in the context of applied research • Write statistical reports on experimental
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cells or electrolyzers. Utilizing innovative, automated characterization techniques we evaluate the catalyst’s performance. This enables the examination of numerous materials in a short time and thus
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knowledge and practical experience in the field of radiation detectors. Experience in the design and performance optimization of neutron detectors is highly advantageous. You work methodically and demonstrate
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10.08.2021, Wissenschaftliches Personal Positions in the Formal Methods for Software Reliability group of TU Munich led by Prof. Jan Kretinsky: - postdoc in the area of quantitative verification