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

Universite de Montpellier; France; On-site; EUR 25,000 - 27,000; Full time

Job summary

Universite de Montpellier invites applications for a postdoctoral researcher in the Laboratory of Mechanics and Civil Engineering (LMGC) to develop and apply machine-learning potentials for silicate interfaces and study ion-water interactions. The project integrates molecular simulation, statistical physics, and experimental characterization, with access to national HPC resources.

The position focuses on creating ML-based descriptions of complex interfaces, running extensive MD simulations, and

Qualifications

• PhD in Physics, Theoretical/Computational Chemistry, Materials Science, or Computational Mechanics.
• Experience developing ML potentials for materials.
• Experience running large-scale MD simulations and applying enhanced sampling methods.

Responsibilities

• Develop and validate ML potentials (MACE, DeepMD) for silicate systems.
• Perform large-scale molecular dynamics simulations (ab initio and classical).
• Use enhanced sampling methods (e.g., metadynamics) to explore free energy landscapes.
• Connect electronic structure calculations with ML to quantify molecular-scale mechanics and macroscopic degradation.

Skills

ML techniques

Programming

Collaboration

Education

PhD or equivalent

Tools

MACE

DeepMD

Molecular dynamics

Metadynamics

Job description

Organisation/Company Universite de Montpellier Department Human Resources Research Field Chemistry Physics Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application Deadline 15 Nov 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Other EU programme Reference Number 2026-C0001 Is the Job related to staff position within a Research Infrastructure? No

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

Requirements

Research Field Physics Education Level PhD or equivalent

Skills/Qualifications

PhD inPhysics, Theoretical/Computational Chemistry, Materials Science, or Computational Mechanics

Work Location(s)

Company/Institute Laboratoire de Mécanique et Génie Civil (LMGC) Country France Geofield