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. The Department of Mathematics and Computer Science, Hessain.AI research group “Artificial Intelligence – Deep Decision Support Systems”, led by Prof. Dr. Martin Becker, is currently accepting applications for a
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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theoretical ecology, geosciences, applied mathematics, environmental physics, or a related field. Research experience in numerical modelling, preferably with knowledge of either eco-evolutionary models and/or
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soon as possible. The position is within the Math+ project "Anisotropic microfluids -- fluctuations, control, effective models and their numerics “. Here, we study anisotropic microfluids and the effect
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(SDPs). You will design climate change mitigation scenarios that respect both climate targets and sustainable development goals using the REMIND model, one of the world’s leading integrated energy-economy
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simulation, with strong skills in mathematics Highly proficient in Matlab/Simulink for system modelling Experience with (stationary) battery storage systems is required Prior exposure to HIL systems is a
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will design climate change mitigation scenarios that respect both climate targets and sustainable development goals using the REMIND model, one of the world’s leading integrated energy-economy-climate
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Job posting (PHY 06/2025) The Leibniz Institute for Baltic Sea Research Warnemünde (IOW) has a temporary vacancy starting 01.01.2026 for a Postdoctoral position in regional ocean climate modeling in
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timings) affect the metabolome and proteome of rapeseed seeds. Your findings will serve as molecular fingerprints to support Deep Learning models for hybrid development. Whom we are looking for: An early
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 1 month ago
. The successful candidate will integrate multiscale first-principles modeling, sparse symbolic regression, and adaptive experimental design in self-driving laboratory settings to elucidate both desired catalytic