PhD Title: Applying machine learning to understand photoprotection: how do triazine-based UV-filters really work?

PhD Supervisor: Nick Hine

Ultraviolet radiation (UVR) has far-reaching consequences on life such as skin cancer in humans and damage to photosynthetic machinery in plants. This project will study the fundamental mechanisms that provide naturally-occurring molecules with photoprotective properties, allowing them to absorb UVR and dissipate it harmlessly as heat. We will harness the power of Machine-Learned Potential Energy Surfaces to accelerate electronic structure calculations based on Time- Dependent Density Functional Theory, which are accurate but far too slow for dynamics. This will enable calculations of properties such as excited state lifetimes in a complex solvent environment. One main target of this will be triazine-based UV filters found in commercial sunscreen formulations.