Postdoctoral Position 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 postdoctoral position within the new European Innovation Council (EIC) Pathfinder Open project IONFLUX. The position is one year long with the possibility of one additional year extension. The successful candidate 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 researcher will contribute to a coordinated programme of AI-guided design of NaI-AlCl₃-BiI₃ catholytes. Activities will include:. - Atomistic simulation and dataset development: Perform, analyze and curate density functional theory-based molecular dynamics (DFT-MD) simulations of catholyte compositions. - Predictive modelling: Develop and evaluate graph neural networks and other machine learning approaches to predict ionic conductivity, viscosity and bismuth nanocluster formation energetics. - Composition optimizat