Artificial Intelligence surrogate models for 2D plasma turbulence

We are offering a 6-month internship focused on the computational modelling and analysis of 2D plasma turbulence. Plasma turbulence is a key phenomenon in plasma physics, impacting systems ranging from fusion reactors to space and astrophysical plasmas. It plays a critical role in the transport of energy and particles, making its study essential. To accurately understand this transport, extensive simulations are often needed to collect sufficient data and capture rare events, but these simulations can be computationally expensive. In this internship, we will investigate how advanced Artificial Intelligence (AI) techniques can be applied to develop more efficient surrogate models for 2D plasma turbulence, reducing computational costs without compromising accuracy.

The candidate will be involved in both the theoretical and computational aspects of the research. The work will be based on an existing AI framework developed at M2P2 for the Hasegawa-Wakatani model [1]. The candidate will have to get familiar with the existing tools and develop additional features for enriching the AI surrogate model with essential aspects of the underlying fundamental physics.

Throughout the internship, the candidate will gain deeper insight into advanced plasma physics concepts, learn cutting-edge numerical techniques, and develop valuable skills in computational science and AI. The candidate is expected to make significant contributions to ongoing research and gain experience in a high-impact area of plasma physics.