Ryan originally began studying for a Bachelor’s degree in Physics with Astronomy at the University of Liverpool, before switching to the integrated Astrophysics M.Phys course in his second year and graduating in 2022.
His Master’s project investigated the influence of dark matter halo assembly history on the AGN gas expulsion and growth of supermassive black holes in Milky Way sized galaxies. The project utilised the cosmological hydrodynamical EAGLE simulations, focusing particularly on a process known as ‘genetic modification’.
Ryan joined the LIV.INNO CDT in October 2022, in which he will be based in the Astrophysics Research Institute at Liverpool John Moores University. He will be applying machine learning techniques, in conjunction with state-of-the-art gas-dynamical simulations such as EAGLE-XL and IllustrisTNG-300, in order to disentangle the complex relationships between the diverse present-day populations of galaxies and their dark matter halos. The resulting machine learning models will then be used to create mock galaxy catalogues that can be compared to ongoing and forthcoming observational “megasurveys” such as WAVES, DESI (spectroscopic) and LSST, Euclid (deep imaging).