Postdoc: ML Potentials for Silicate Interfaces (MD/HPC)

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

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