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(100%) Published: 26.11.2025 Limitation:Temporary (2 years) Contract:TV-L Your tasks Analyse spatial transcriptomic and image datasets Develop predictive models for diagnostic purposes Design research
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engineering, and quantitative live-cell imaging to probe and model these processes. By combining stem cell biology with cutting-edge microscopy and physical concepts, we aim to establish a predictive framework
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influenced corrosion (MIC) in marine environments. It uses AI-supported models, Bayesian data fusion, and real-time sensor data integration. Your responsibilities include: Development of a digital twin (DT
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | 28 days ago
for candidates with a background in high-redshift galaxy observations. Additional experience in the theoretical modelling of high-redshift galaxies and/or supermassive black holes is welcome. The successful
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Models (LLMs) to create the methodological foundation for next-generation AI systems that clinicians can truly understand and trust. All components will be released as open-source software and reusable
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sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal experiments group (You
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Potsdam, Brandenburg | Germany | 28 days ago
model analyses with reanalysis data to quantify the direct and causal effects of sea ice changes on large-scale circulation patterns and extreme events. Your Tasks Set-up and performance of large-ensemble
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content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all prior to any training. Our team includes
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Experience in Palynological, Archaeobotanical and Geographical approaches, Modelling and programming, as well as an interest in Historical, Social and Anthropological questions. Active participation in
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, natural and anthropic archives, and evaluate existing model simulations and scientific narratives on biodiversity loss. These studies will be conducted in part by the position holder themselves and