Investigating the faint radio population in the Lockman Hole with novel Machine Learning techniques

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This project will utilise new machine learning techniques to decompose the relative contributions of Active Galactic Nuclei and Star Forming Galaxies to faint radio sources in the sub-mJy flux density range. This study will be carried out using joint e-MERLIN and VLA observations of the Lockman Hole. The result is a high resolution map of the target field, due to the long baselines of e-MERLIN, augmented by the excellent sensitivity of the VLA. Using these observations to morphologically identify these two sources in this flux range will provide evidence indicative of the global star formation rate history of the universe, as well as complimenting the results of similar work conducted in the GOODS-N field.