In her PhD research, Daniela is working on the development and application of machine learning techniques to study charge transport and defect dynamics in semiconductors and related materials. She is particularly interested in polaron quasiparticles — how they form, how they move, and the quantum effects they induce in materials.

Her work also includes topics in surface science, such as surface polarons, adsorption, and chemical reactions at material interfaces. In addition, Daniela is involved in nonadiabatic dynamics and contributes to the development of software tools that support accurate and efficient quantum simulations.

We are excited to have Daniela on board and look forward to exploring new scientific challenges together!