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Offer Description Development of atomistic ab-initio simulations and machine learning models for the study of phonon transport, phase transitions, and structural optimization of phase change materials
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processes, multimodal data fusion, physics–ML hybrid modelling (from CFD to atomistic simulations), and AI-assisted hypothesis formulation. MSCA Doctoral Candidate eligibility criteria Applicants must comply
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the study of nucleation mechanisms, the analysis of out-of-equilibrium energy and thermodynamic balances, and the validation of results by comparison with experimental data and atomistic simulations
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