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numerical fluid mechanics, scientific computing, or model-order reduction, who is willing to engage in innovative and interdisciplinary research questions. The successful candidate will also have the
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with at least 3 years of research experience in a field related to numerical fluid mechanics, scientific computing, or model-order reduction, who is willing to engage in innovative and interdisciplinary
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theoretical models and methods as well as in implementing numerical optimization techniques Interest in working closely with experimentalists Detailed knowledge of quantum physics and experience with quantum
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state. The project will specifically investigate the role of endogenous retroelements in this context. Immune-functional consequences will be studied using in vivo mouse models, and in cell culture
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state. The project will specifically investigate the role of endogenous retroelements in this context. Immune-functional consequences will be studied using in vivo mouse models, and in cell culture
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neuroimaging and mc-tCS simulation approaches based on realistic head volume conductor models using modern finite element methods as well as sensitivity analysis. The new methods will be applied in close
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considered. The ideal candidate will have a background in immunology, tissue biology or cellular metabolism. Experience in working with animal models, cell isolations from tissues (lung, intestine), human
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
Area of research: Scientific / postdoctoral posts Starting date: 01.07.2025 Job description: Postdoc (f/m/d): Machine Learning for Materials Modeling With cutting-edge research in the fields
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bases and instruments in terms of their efficiency and incidence Applied game-theoretic modelling based on 1) and on numerical estimates of the benefits that potential donor countries derive from
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on the influence of Alzheimer’s disease and aging on changes in cognitive functions in humans. The project combines cutting-edge technologies from genetics, proteomics and statistical modeling to understand