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identify the necessary solutions. The findings should also remain valid under different climate change scenarios. With its global state-of-the-art energy system model, ICE-2 at Forschungszentrum Jülich
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) software for topology-informed biomedical image analysis and large foundation models. You will be responsible for Develop new machine learning algorithms for microscopy image analysis problems (2D/3D/4D/5D
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now. As a result of this success and the dedicated community of plant enthusiasts, millions of plant observations are available, their numbers growing. These observations are useful for modelling
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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
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histological validation within murine cancer models. We offer an association with the Collaborative Research Centre 1450 “Insight – Multiscale imaging of organ-specific inflammation” graduate school
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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expertise in employing synthetic microbial communities, gnotobiotic mouse infection models as well as in molecular microbiology of gut microbiota and enteric pathogens. The TUM School of Life Sciences
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Specifications. The PhD topic consists of two parts, the weighting of which can be adjusted. First, natural frequencies of different UAV categories for different power settings shall be modelled. Second, based
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frequencies of different UAV categories for different power settings shall be modelled. Second, based on mesoscale fluid dynamic simulations, microclimatic and turbulence modelling procedures in urban
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support the development of a European energy system model by benchmarking future technologies and optimizing their representation within the FINE optimization modelling framework ( https://github.com/FZJ