Samuel Boobier joined the Hirst group in June 2021 as a Postdoctoral Researcher. His project focusses on using machine learning to design and develop sustainable process in chemical synthesis. He completed his PhD at University of Leeds, working with AstraZeneca on the solubility prediction of small pharmaceuticals in water and organic solvents. Other research interests include: predicting reactivity; DFT and molecular modelling; hand curation of chemical descriptors for machine learning; and the interaction of the machine model and human expert in chemistry predictions.