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position within a Research Infrastructure? No Offer Description Activities and context: The fellow will develop machine-learning interatomic potentials (MLPs), trained on density functional theory-DFT data
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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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with national/international collaborators from the ODUST consortium. • Access to HPC resources (e.g., IDRIS) for large-scale simulations. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR5299
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matter physics, with a staff of 450, including 175 researchers and lecturers. The MEM laboratory (CEA Grenoble) conducts research on the exploration of materials and devices using advanced simulation
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; previous experience as local contact at synchrotron XAS beamlines; knowledge of advance characterization techniques like XANES simulation and ab initio calculations (e.g. DFT). Good time management skills
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to investigate and develop novel ceramic electrolytes for next-generation composite solid-state batteries. Particularly halides and sulfides are of interest. By integrating atomistic simulations with experimental
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, please contact Duy Le at [email protected]. Responsibilities: The Postdoctoral Associate’s Responsibilities include but are not limited to: Performing computational modeling using DFT, GC-DFT, MD (AIMD
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semiconductors, including conjugated polymers. • Perform molecular dynamics simulations to investigate structural organization and molecular connectivity. • Carry out electronic-structure calculations
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RXN). Familiarity with reaction condition prediction and reaction yield optimization. Exposure to quantum chemistry (DFT) and molecular simulations is a plus. Experience with cloud computing and/or high