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Field
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individuals holding a Master of Science degree in condensed matter physics or materials science, with a focus on numerical simulations - Prior experience with theoretical and or computational project work is
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 26 days ago
profile # Ph.D. in the field of Physics, Chemistry, Computer Sciences or Applied Mathematics or related field # Background in mathematical surrogate modeling and machine learning # Experience or familiarity
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a unique range. Institute of Material and Process Design The Institute of Material and Process Design is dedicated to the sustainable and ecological development of innovative materials and
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site in Heidelberg, invites international students holding a Master’s degree in (molecular) biology, (bio-)chemistry, (bio-)physics, computational biology, computer science, epidemiology / public health
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: “Optimizing microwave plasma-based reduction of metal oxides” under the supervision of Prof. von Keudell, Chair for Experimental Physics – Reactive Plasmas at the Faculty of Physics and Astronomy, Ruhr
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, physics or a similar area - very good programming skills in Python - good prior experience with neural networks using common Python-ML libraries such as PyTorch - background knowledge in computational
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07.04.2026, Academic staff PhD position at the interface of computational physics, machine learning, and experimental reactor design. The project focuses on developing PINN-based simulations
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7 Apr 2026 Job Information Organisation/Company Technische Universität Dortmund Department Department of Physics Research Field Physics Computer science Geosciences Mathematics Chemistry Researcher
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computing, and synchrotron-radiation experiments. The goal is to explore physics-informed self-supervised learning approaches (e.g., deep image priors, GANs) and iterative methods, combined with multi-scale
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computing, and synchrotron-radiation experiments. The goal is to explore physics-informed self-supervised learning approaches (e.g., deep image priors, GANs) and iterative methods, combined with multi-scale