Joseph Abbott (Joe) joined lab COSMO at EPFL in October 2022. He is currently working on machine learning the electron density using physics-inspired structural representations of molecules and materials. His research interests span machine learning, quantum chemistry, electronic structure theory, molecular dynamics, quantum dynamics and battery modelling, as well as the development of open-source scientific software.
Joe started his undergraduate MSci master's degree in Chemistry at the University of Bristol in 2016. In his third year, he studied abroad at the University of Washington, Seattle. Here he conducted undergraduate research under the supervision of Xiaosong Li, focusing on the use of electronic structure theory methods to probe the spectroscopic signatures of computationally-designed noble gas-doped nanodiamonds. Upon his return to the UK, Joe took up a summer research position at the STFC neutron and muon particle accelerator facilities near Oxford. There he was involved in the development of a scientific software package that analysed experimental quasi-elastic neutron scattering data produced on-site. Returning to the University of Bristol in October 2019, for the fourth year of his MSci degree, Joe joined the group of Fred Manby. His master's thesis was concerned with the computational modelling of the quantum dynamics of photosynthetic excitonic energy transfer and involved producing some supporting open-source software.
After graduating from the University of Bristol in 2020, Joe joined the Quantum Mechanics group of BIOVIA, Dassault Systèmes in Cambridge. Here he undertook a year-long industrial placement, working on algorithm development for modelling atomistic chemical reactions and incorporating this into a multiscale simulation method for modelling the growth of the solid electrolyte interphase in lithium-ion batteries.