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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 3 days ago
AI in biology. The successful candidate will design and implement physics-informed machine learning frameworks and predictive models to uncover how gene expression and mechanical forces interact
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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new vegetation model. The new EEO-based vegetation model should then also be used to predict future transitions and biome shifts to ultimately answer the question to what extent C4 grasslands
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partner from data 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
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vegetation model. The new EEO-based vegetation model should then also be used to predict future transitions and biome shifts to ultimately answer the question to what extent C4 grasslands, savannahs and their
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Universities of Tübingen and Hohenheim. The focus research unit brings together paleobiologists, earth scientists and earth system modelers who jointly aim to disentangle hydroclimate and enigmatic biodiversity
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methodologies. The focus is on across-organ imaging, ranging from non-human primate (NHP) models to human applications. You will contribute to the development and application of state-of-the-art MRI techniques
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of hydrological connectivity of soil moisture using gridded soil moisture data sets and data-driven approaches (e.g., complex network methods) Develop models to predict gatekeeper locations and their relationship
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technologies for batteries. Your tasks in detail: Develop innovative quantum computing approaches for the simulation of electrochemical processes in complex electrode materials Connect quantum-enabled models
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, effort, and experimental expenses, and to provide data that is unachievable through experiments. Chemical kinetic models form the basis for a predictive tool, used to understand, optimise, and engineer