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the utility and the robustness of different explanation strategies. A large focus of this project will be on leveraging novel and interpretable approaches in applied domains such as algorithmic fairness and
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the latest advances in AI to identify factors in pregnancy, labour and in the early neonatal period that represent increased risks for CP. We will develop novel AI algorithms for the analysis of physiological
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evaluation. Previous knowledge of belief/trust for vehicular cooperative perception is a distinct advantage as is experience with algorithm development and networking simulation. Candidates should have
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the distribution of expression levels in tens of thousands of single cells. In this project, we will utilise state of the art single cell omics to decipher the biological processes underpinning therapeutic rAAV