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Biology Research Centre at Human Technopole combines computational and experimental techniques to study how tumours arise and evolve. Our goal is to measure the evolutionary processes in human cancers
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recognition, automation science, complex systems, robotics, machine learning, computer vision, natural language processing, biometrics, medical imaging, social computing, and AI hardware. CASIA is the first
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processes; Develop and supervise the establishment of a world-class research programme in translational epidemiology; Foster a diverse and nurturing research environment through leading and mentoring a team
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at elucidating the fundamental molecular mechanisms underpinning diverse pathophysiological processes; Develop and supervise the establishment of a world-class research programme in health data science; Foster a
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biology applied to human health. However, priority will be given to research programmes in one of the following areas: Computational Imaging & Computer Vision. Developing novel algorithms for quantitative
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) models. Dive into diverse deep learning models to process complex datasets, including omics, phenotypic and imaging data, to reconstruct cancer evolution and discover new cancer biomarkers. Be
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cell and spatial genomics approaches and advanced imaging Computational analysis to study neurodevelopmental dynamics at the single cell level. Analyse and integrate imaging data with molecular