CENTRALE LYON - Postdoctoral Researcher Position Deep Learning for Functional-Oxide Growth Video-to-Spectrum Prediction by RHEED / XRD Fusion

PROJECT OVERVIEW

We are looking for a highly motivated Postdoctoral Researcher to develop innovative deeplearning models that predict the structure of functional-oxide thin films directly from their growth dynamics. Positioned at the interface between Artificial Intelligence and materials physics, the OXYD-IA project aims to design a deep model able to predict the final X-ray Diffraction (XRD) spectrum of an oxide thin film from the sole Reflection High-Energy Electron Diffraction (RHEED) video recorded during its growth by Molecular Beam Epitaxy (MBE).

The resulting tool will open the way to predictive, in situ control of oxide epitaxy – a process today dominated by a costly trial-and-error approach, in which the structural and functional properties of the films are only validated ex situ. You will join a genuinely multidisciplinary collaboration between the INL (Institut des Nanotechnologies de Lyon), which provides the operando experimental data and materials-physics expertise, and the LIRIS (équipe Imagine), which provides the deep video-learning and probabilistic-modelling methodology – both at École Centrale de Lyon.

A high-impact opportunity. AI for experimental physics is a fast-growing field, and OXYD-IA offers a genuine first-mover advantage within it: you would work on a unique, unpublished dataset of paired RHEED videos and XRD spectra to build one of the first video-to-spectrum models with calibrated uncertainty for oxide growth. By learni