142 algorithm-development-"Prof"-"Prof"-"Washington-University-in-St" Postdoctoral positions in Germany
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connect to our group’s work and how this position supports their career development goals. Possible research topics include (but are not limited to): Optimization algorithms for machine learning (stochastic
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Your Job: Design and development of a modular high throughput sample environment for chemical hydrogen storage investigations under realistic conditions Design, optimization, and testing of sample
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for the discovery of new physics experiments) Developing, benchmarking and advancing state-of-the-art AI-driven exploration, optimization, and search algorithms in extremely complex and enormously large spaces
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on the creation and application of predictive simulation models Collaboration on the development of data processing and fusion algorithms Collaboration on the virtual modeling of marine structures Conducting and
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division 8.5 Planning, performing, and evaluating in-situ/4D computed tomography experiments Developing software for the quantitative evaluation of various image data sets (algorithms for detecting volume
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27.09.2025, Wissenschaftliches Personal We are seeking a PhD or Postdoctoral researcher to join the AI in Orthopaedics group (TUM & TUM University Hospital). The position focuses on developing
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Helmholtz-Zentrum Berlin für Materialien und Energie | Berlin, Berlin | Germany | about 2 months ago
on the data recorded in the team, you will develop and test machine learning algorithms for perovskite tandem solar cells' energy yield and degradation Data cleaning and preparation Assisting integration
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of MIRMI. At the Geriatronics Research Center – part of MIRMI and located in Garmisch-Partenkirchen – we develop cutting-edge solutions to enhance quality of life in older age and improve the efficiency
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- conducting processors with respect to practical short-depth (NISQ) quantum algorithms Cooperate and actively work with experimental partners developing quantum processors using these technological platforms
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project within the SusMax network focused on developing interpretable machine-learning frameworks for kinetic multiphase reaction-network discovery in the catalytic conversion of renewable feedstocks