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Technologien (IWT), Thyssenkrupp Steel Europe AG, Oulun Yliopisto and Ovako Sweden AB, to connect modelling insights with process development and alloy design Contribute to scientific publications, conference
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first-principles (ab initio) simulations, computational materials science, mineral physics, or related areas. Experience with density functional theory simulations, high-performance computing
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molecular simulation techniques (density functional theory, molecular dynamics, ab initio molecular dynamics) and in developing machine learning interatomic potentials and can apply these to uncover atomistic
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absorption fine structure), development of data-analysis approaches and computer software for simultaneous structural refinements using multiple types of data combined with ab initio theoretical modeling
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and machine-learning potentials for planetary materials. Curating and generating large-scale ab initio datasets across wide pressureâ“temperature regimes. Designing and training advanced machine
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knowledge of solution chemistry, chemical thermodynamics, and chemical equilibria. • Basic knowledge of quantum chemistry and ab initio computational methods (electronic structure calculations, structure
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profile. This is a permanent, part-time position offered on a variable-hours contract. About you You will have substantial experience of teaching Dutch in Higher education, from ab initio courses
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equations – strong foundations in quantum electrodynamics (QED) are a significant bonus. The role of RF will focus on developing ab initio theory and developing software to describe and study groundbreaking
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experience with molecular simulation, ab-initio, or macroscale modeling is not necessary, nevertheless, will be considered a strong plus. TU Delft (Delft University of Technology) Working at TU Delft means
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materials, leveraging informatics-driven approaches (machine learning, high-throughput ab initio, data-driven discovery) alongside advanced computational methods (e.g., DFT+DMFT, GW, quantum embedding