Skills - Python; FORTRAN; Matlab
Academic Domains - Chemistry; Materials; Crystallography; Machine Learning; Optimisation
Phillip Maffettone is a post doctoral research associate utilising artificial intelligence and robotics in the search for advanced functional materials. He is presently based in the Chemistry Department at the University of Liverpool. His specific work involves machine learning and representation development for crystalline systems; high-throughput characterisation and analysis; and Bayesian optimisation of robotic experimentation.
Previously; he developed structure solution approaches for disordered materials systems from total scattering data. Phil is familiar with Python; FORTRAN; and Matlab. He has worked on a range of computational projects across the physical sciences and engineering; combining domain expertise with scientific programming.