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assessment of chemical plants using HAZOP analysis Use of process modeling and simulation to enhance quantitative assessments Use of machine learning to support HAZOP discussions with the aim of obtaining a
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transport, microbial systems, or circular bioprocesses. You will contribute to developing and applying novel modeling strategies, AI-enhanced simulations, and computational workflows to explore biological
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-language models, or diffusion models to simulate and design complex urban traffic environments? Do you want to shape the next generation of data-driven mobility intelligence with your creative ideas and
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investigates how the gut microbiome shapes cognition and neuroinflammation during menopause, with a strong emphasis on computational modelling. We will reconstruct and simulate microbial metabolic networks
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | about 2 months ago
research groups, and the application procedure, please visit the IMPRS website . The ACR and CRA research divisions at the AEI in Potsdam operate three high-performance compute clusters to model
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-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based recommendations
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. The research group Molecular Modeling / Section III are currently looking for a committed PhD Student to start on 15/01/2026. PhD Student (m/f/d) The Leibniz Institute for Food Systems Biology at the Technical
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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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Your Job: You will work as a doctoral researcher within one of four interdisciplinary PhD projects in the Simulation and Data Lab Digital Bioeconomy. Each project combines natural sciences with
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Your Job: Modeling and characterization at molecular level of selected biological processes by performing classical molecular dynamics, and employing enhanced sampling methods and machine learning