[M/F] Postdoctoral Researcher in Machine Learning Potentials and Molecular Simulation

id="offer-description" class="ecl-u-type-heading-2 ecl-u-mt-none ecl-u-mb-l">Offer Description - work environment: The LMGC and L2C (Montpellier) conduct interdisciplinary research in condensed matter physics, mechanics, and materials science. The MINT project (Multidisciplinary Insights into Nanopore pressure due to ion Trapping) brings together complementary expertise in molecular simulation, statistical physics, and experimental characterization. Integrated into an international network, the candidate will benefit from a collaborative environment and access to national HPC resources (IDRIS, TGCC, CINES). - main mission: D evelop and apply machine-learning potentials (MACE) to describe complex silicate gel/water/ion interfaces and quantify the molecular origins of disjoining and ion-correlation pressures. - activities: . -Development and validation of ML potentials (MACE, DeepMD, etc.) for silicate systems. -Performing large-scale molecular dynamics simulations (ab initio and classical). -Using enhanced sampling methods (e.g., metadynamics). -Connecting electronic structure calculations and ML to molecular-scale mechanics, up to the macroscopic degradation of materials. The net monthly salary is between €2,200 and €2,380 . The contract duration is 18 months. Where to apply E-mail [email protected]. Requirements Research Field Physics Education Level PhD or equivalent . Skills/Qualifications. PhD in Physics, Theoretical/Computational Chemistry, Materials Science,