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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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larger simulation environment that evaluates the aviation system of the future. The PhD should consider: Research: Characterise how new aircraft types differ in performance from current traffic, and what
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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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simulations, the candidate will investigate the emergence of turbidity maxima, the formation of fluid mud layers, and the mechanisms governing sediment retention in estuaries. Particular attention will be paid
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ice, using a framework consisting of an ocean Large Eddy Simulation (LES) and a Discrete Element Model (DEM) of sea ice. Results from these simulations will be validated against a combination of in-situ
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have: MSc in engineering or similar discipline by the start date of the position Experience with mechanical modeling and simulation Experience in computer programming/scripting (e.g., C++, Python, Matlab
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engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and
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to solutions that really make a difference. For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge
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researcher. The Veldhorst group is a pioneer in quantum computing and simulation in germanium. They have demonstrated the first single-hole qubit, enabled two qubit logic in germanium, executed quantum
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TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe