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Functional Theory (DFT) Familiarity with artificial intelligence methods Good knowledge of electronic structure methods Experience with Linux, Git and related tools Knowledge in the field of high-performance
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Description In this project, we develop machine learning models for prediction of optical properties of chiral molecules based on DFT/CCSD data which we calculate ourselves. We include derivative information by
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combines state-of-the-art computational multiscale modelling (using DFT/TDDFT methods, collision theory, molecular dynamics, stochastic dynamics, Monte Carlo and analytical methods) and its thorough
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combines state-of-the-art computational multiscale modelling (using DFT/TDDFT methods, collision theory, molecular dynamics, stochastic dynamics, Monte Carlo and analytical methods) and its thorough
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of radionuclides on clay mineral surfaces using DFT Kinetic Monte Carlo simulations with activation energy barriers as input to simulate large-scale interactions of nuclides with surfaces Preparation and