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Domaine Matériaux, physique du solide Contrat Stage Intitulé de l'offre Stage BAC+5 Simulation multi-échelle H/F Sujet de stage Ab initio free-energy landscape of lithiated graphite Durée du contrat
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dynamics (MD) simulations capable of probing hydrogen diffusion and trapping at interfaces in the presence of tramp elements with near-DFT accuracy Collaborate closely with a broad team of researchers from
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predictive MD simulations capable of resolving atomic-scale LCI mechanisms with near-DFT accuracy Investigate how silicon suppresses LCI, including its effects on grain boundary site competition and the
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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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Description of Group/Project: The Theoretical and Computational Nanoscience group at ICN2 develops theory, models and large-scale simulation tools for quantum transport, spin dynamics and emergent computing in
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that can be benchmarked through physical experiments or computational simulations. The project is funded by the Research Council of Norway and is a collaboration between NTNU and Norsk Regnesentral
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for molecular magnetic materials lags behind these experimental breakthroughs. DFT fails to capture strong correlation, while wave function-based methods are computationally prohibitive for strongly-correlated
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(DFT, Molecular Dynamics Simulations, Docking, etc.). Proficient in oral and written English. Documented skills in academic writing. Ability to plan research work and critically assess and discuss
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and validate its accuracy against previous benchmarks for small molecules like PtH. This approach is general and can be directly combined with EOM-CC embedded in point charges, or in periodic DFT
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simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification, Bayesian optimization