Dr Charlie Adams is a Research Software Engineer in the Department of Chemistry, working within the Matta Group. He is currently developing scalable computational solutions for the discovery of new polymers for electronic applications. His expertise spans quantum chemistry, AI model development, and software engineering.

Charlie completed his PhD at the University of Sheffield in collaboration with Rolls-Royce, where he applied quantum chemistry to uncover fundamental structure–property relationships for sustainable aviation fuels. This work enabled predictive modelling of fuel behavior within next-generation engines. He subsequently spent a year in the nuclear industry, where he modelled chemical and logistical processes to support the design of future facilities.

More recently, Charlie worked at the AI-driven drug discovery startup Kuano for a year and a half, collaborating with Newcastle University to develop machine learning models that predict key electronic properties. During his time there, he built high-throughput workflows for generating large quantum mechanical datasets and training graph neural networks (GNNs). These models were then deployed across Kuano’s drug discovery platform using modern software engineering practices.

Research

• Materials Discovery
• Quantum Chemistry
• Machine Learning Model Development
• High-throughput Computational Screening

Charlie works at the interface of chemistry, physics, and engineering to accelerate materials discovery. His research focuses on scaling quantum chemistry methods and integrating them with machine learning to address complex, application-driven challenges-from catalysis to drug discovery. By combining high-throughput computation with ML models, he enables the rapid screening and design of functional materials for sustainable technologies and industrial processes.