We develop theory, computational methods, and associated software, to enhance our understanding of chemical systems and processes. The University supports us with high-performance computing resources.
We make leading contributions in wide-ranging applications that connect to other important themes in the School of Chemistry and Chemical Engineering, such as materials, catalysis, and health.
These applications use the group's expertise in simulation methods, covering a wide range from electronic structure to the large-scale behaviour of complex systems. They also involve process integration and systems analysis. The work involves developing machine learning and using large-scale data to improve our understanding of chemical systems and processes.
As the academic lead of the Physical Sciences Data Infrastructure, we develop national facilities to drive data science and machine learning methods across the whole discipline.
