PhD Studentship under Supervision of Dr Seán Kavanagh

A PhD studentship in computational modelling (DFT & MLIPs) of solid-state energy materials offered by the Department of Chemistry at the University of Cambridge. The research team uses state-of-the-art computational methods to design and develop next-generation materials, primarily targeting energy applications including solar cells, batteries, thermoelectrics and photocatalysts. The work sits at the intersection of materials science, chemistry, physics and artificial intelligence, deploying techniques from quantum chemistry, solid-state physics and machine learning to understand atomic-level properties of materials. The project is flexible to the student's interests and skillset, with one target project focusing on using advanced methods to model performance-limiting defects in disordered solar cell materials. This work will require minor but impactful methodology developments that will help revolutionise modern materials modelling strategies. The studentship is for 3.5 years and covers home fees and maintenance. Experience with computational methods (Python/coding, machine learning, DFT) is beneficial but not required, just a willingness to learn and passion for research.