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generation, targeted atomistic simulations, structural descriptor extraction, and predictive models. The work will aim to establish links between local pore geometry, structural disorder, sodium adsorption
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, GemNEt, eSEN…..) for accurately predicting Material properties (especially adsorption properties). Experience with ML models applied to materials science alongside background in AI-generative diffusion
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simulations (MD), including the development or use of appropriate interatomic potentials to study adsorption, diffusion, and thin-film growth, as well as ion–matter interactions during deposition, whether ion
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