PhD in AI-Guided Materials Discovery for Batteries

id="offer-description" class="ecl-u-type-heading-2 ecl-u-mt-none ecl-u-mb-l">Offer Description The Multi-Scale Modeling Laboratory (SMaLL) at Politecnico di Torino invites applications for one PhD position and one postdoctoral position within the new European Innovation Council (EIC) Pathfinder Open project IONFLUX. The successful candidates will work towards the development of computational and artificial intelligence methods to guide the discovery of adaptive catholytes for sodium batteries. The research combines atomistic simulation, graph neural networks, Bayesian optimization and experimental feedback, agentic AI with the goal of translating molecular understanding into actionable materials design rules. We welcome applicants with complementary backgrounds in computational physical sciences, engineering and machine learning who are interested in advancing materials discovery for energy storage. The PhD researcher will develop a doctoral project (with total duration of 3 years) connecting molecular simulation with machine learning for adaptive molten catholytes. The work will investigate how composition affects local structure, ionic transport and nanocluster formation, and how this information can be used to guide materials discovery. Where to apply E-mail [email protected]. Requirements Research Field Engineering » Computer engineering Education Level Master Degree or equivalent . Skills/Qualifications. We are looking for applicants with:. - A Master’s degree