PhD Position at INRIA and IFPEN research Institutes (France)

The aim of this project is to apply recent enhanced sampling algorithms and to develop Machine Learning (ML) techniques to identify some fundamental mechanisms and their corresponding energy barriers involved in heterogeneous catalysis. More precisely, the evolution of chemical systems during catalytic reactions is well described by a Hamiltonian dynamics, possibly with stochastic perturbations to impose temperature, where the forces are computed using quantum models (so-called Ab Initio Molecular Dynamics, AIMD). The numerical integration of this dynamics is however expensive, hence advanced algorithms are needed to accelerate it and to identify more efficiently catalytic mechanisms.