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) in Chemistry, or other relevant scientific discipline (e.g. Physics, Materials Science). Candidates with experience in ab initio electronic structure methods, scientific programming, or scientific
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: Machine Learning Molecular Dynamics. The project involves the development and application of machine learning methods that enable a major boost of the time and length scales accessible to ab-initio/first
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atomistic simulations, however these suffer from inconsistent accuracy, particularly for fluoride-containing salts and complex mixtures. On the other hand, ab-initio simulations which explicitly handle
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., Mumax3, Vampire, etc.) • Open-source ab initio codes (e.g., KKR, VASP, Quantum-Espresso, etc.) • Coding languages (e.g., Fortran, C/C++, Python, etc.) • Previous lab experience, especially in scattering