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Field
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learning potentials can overcome typical bottlenecks of empirical potentials for simulating dislocations, cracks and hydrogen diffusion near precipitates embedded in ferritic iron. While considerable
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and quantifying the HE mechanisms, since hydrogen is challenging to detect experimentally. Machine learning potentials can overcome typical bottlenecks of empirical potentials for simulating
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collide, condense and evaporate. Guided by the results from the field campaigns, a new Microphysics Informed Large-Eddy-Simulation (MiLES) model will be developed. The tested and verified MiLES will be
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molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry partners. Job description At TU Delft, you will contribute to a transformative research
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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Are you eager to perform quantum simulations in a lively, international research group? Do you enjoy creating complex machines that have never existed before? Do you want to explore physics
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21 Jul 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Aerospace engineering Engineering » Simulation engineering Researcher Profile
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Help accelerate the electrification of industry by combining molecular and process-scale simulations for high-temperature thermal energy storage. Job description Carbon-based chemicals are essential
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PhD candidates and postdoctoral researchers. We house or have access to a wide variety of world-class laboratories, among which are the Electron Microscopy Centre , the Geolab , and the Earth Simulation
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, supporting the global energy transition. A significant part of these facilities are housed in the “Earth Simulation Laboratory (ESL)”. Your job As our new Research Officer, you support scientists and students