Final-year PhD student working together with Infineon towards an efficient approach for modelling material properties using machine learning. My research is focused on overcoming computational limits imposed by costly DFT calculations by using neural-network force fields, and on extracting thermodynamical results from those accelerated models of the potential energy hypersurface. I am very interested in differentiable code and its use cases in physics.