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trophoblast cells in a small animal model. The project is part of the new Collaborative Research Center (SFB 1713) “Maternal Immune Activation: Causes and Consequences”. We are seeking a highly motivated and
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, computational model development, data processing, and code implementation in close cooperation with scientists. The position is limited to 3 years. Equal opportunity is an important part of our personnel policy
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) engineering, computer science, or a related field You have very good knowledge of energy technology, energy economics, and energy policy You have already gained initial experience in energy system modeling You
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of paleoclimate modelling, starting as soon as possible. The position is funded for 36 months. Remuneration is in accordance with the German public tariff scheme (TV-L Brandenburg), salary group E 13. This is a
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integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing, computational model development, data processing, and
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energy system model workflows Your Profile: Master’s degree in computer science, data science, natural sciences, economics, engineering, mathematics or a related field of study Huge interest in data
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The Leibniz Graduate School on Aging (LGSA) is a joint program of the Leibniz Institute on Aging – Fritz Lipmann Institute (FLI) and the Friedrich Schiller University (FSU) in Jena. The School calls
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to the computational complexity of climate models, these will be replaced by physics-informed deep learning surrogates in the aforementioned model coupling. The project will initially focus on one main application
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in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages, PyTorch Familiar with foundation models (vision large models or multi
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of new EEG and MEG 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