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support for process development from laboratory to pilot to demonstration scale Working with a wide range of simulation tools such as CFD, numerial optimisation and artificial intelligence Topic-independent
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advantageous but not mandatory: Simulation sciences, ideally modelling microswimmers, Wet-Lab work, Different forms of microscopy Our Offer: We work on the very latest issues that impact our society and are
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synaptic resilience and the reliability of synaptic responses. The work primarily involves mathematical modeling and numerical simulation, but also the analysis of experimental datasets for model validation
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. Required documents CV - including methodological skills Motivation letter Copy of Master’s degree (or proof of expected completion) Master thesis (if available) All academic transcripts Contact information
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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, modelling and simulation in CFD/FEA. Experience with scientific programming (at least Python and C++). Excellent written and spoken English. Very strong team working skills in international, interdisciplinary
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 22 minutes ago
€ if applicable). The PhD funding is for 36 months. Required documents CV - including methodological skills Motivation letter Copy of Master’s degree (or proof of expected completion) Master's thesis
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4‑year PhD position in the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and
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assisted ISAC framework available at the TUM ACES Lab. ▪ Conducting real world experiments to analyze performance deviations between theoretical models, software simulations, and hardware behavior. ▪ Working
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High