Stage : STAGE - Modélisation par intelligence artificielle des combustibles nucléaires à l'échelle atomique H/F
Core
Develop an AI method to describe atomic displacements in disordered nuclear fuels (MOX, U-Mo) to predict material properties.
Role type
Research intern (atomic-scale modeling & generative AI)
Builds
AI models for nuclear fuel simulation
Domain
Nuclear energy, materials physics, atomic-scale simulation
Deliverable
production ML models
Required skills
Molecular dynamics, Python programming, statistical physics, solid-state physics, variational autoencoders
Preferred skills
Machine learning, scientific programming
Technologies
PULSE, LAMMPS, variational autoencoders, molecular dynamics
Responsibilities
Generate atomic configurations via molecular dynamics at various temperatures; test existing atomic descriptors for sensitivity to displacements; propose integration methods for descriptors into the PULSE model.