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atomistic simulations, high-performance computing, and the application of AI-based methods Basic knowledge in photovoltaics and solid-state materials for energy application Ability to work individually and in
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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