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focus of our teams’ efforts over the last couple of decades, seeking insights into pathways steering plaque instability, as well as identifying novel biomarkers improving on clinical routine. A
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Sciences division. This multidisciplinary team utilises a combination of machine learning and mechanistic modelling to derive models and scientific insights from data, which both support and enhance drug
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. This project asks: how do genetic, environmental, and lifestyle factors interact across different ancestry groups to influence CMD risk, and can ancestry-specific insights inform more precise prediction
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omics has made great leaps in terms of multiplexing capabilities and power to decipher spatial patterns of molecules and cells. They provide insight into cell development, micro-environment interactions
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methods in applied mathematics and computational modeling, this specific project aims to uncover new insights into how blood cells form in both healthy and disease states. A key objective is to model
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application of these platforms will focus on translating the developed tools and insights into clinically relevant, novel diagnostic modalities. Requirements Master’s degree in biomedical engineering