Postdoctoral Fellowship in Machine Learning for Turbulent Dynamo Studies at Université Paris-Saclay

The LISN laboratory at Université Paris-Saclay is offering a two-year postdoctoral fellowship focused on machine learning applications for turbulent dynamo studies. This opportunity is part of the ANR MILADY project and is hosted within the renowned CNRS research environment. The research will involve advanced computational physics and machine learning techniques to address challenges in turbulent dynamo modeling. Supervisors include Didier Lucor and Caroline Nore, with additional contact from Sibo Cheng, Junior Professor at École des Ponts, Institut Polytechnique de Paris. The position is ideal for candidates with a strong background in physics, computer science, or related fields, and who possess expertise in machine learning, computational methods, and physical modeling. The LISN laboratory provides a collaborative and innovative research setting, and the project offers the chance to contribute to cutting-edge research at the intersection of physics and artificial intelligence. Funding is provided through the ANR MILADY project, though specific stipend details are not mentioned. Interested applicants should review the attached document for full application instructions and contact the supervisors for further information. This is an excellent opportunity for postdoctoral researchers aiming to advance their careers in computational physics and machine learning within a leading French research institution.