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signs of cardiovascular changes, adaptively model physiological patterns, and identify predictive biomarkers of maternal health. You will develop and apply cutting-edge techniques in: Signal processing
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theory to lightweight on-hardware prototypes, with publications targeted at leading IEEE venues in communications and signal processing, and relevant AI venues. Indicative directions (choose one or combine
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to apply: Please choose Electrical and Electronic Engineering Research Program and Control and Power Group, then indicate Professor Balarko Chaudhuri as a potential supervisor when making the application
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requirements of the role. Please note referees may be contacted at any point in the assessment process. If you upload any additional documents which have not been requested, we will not be able to consider
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research group, which leads pioneering work in multi-sensor navigation, signal processing, and system integrity for aerospace, defence, and autonomous systems. The research will deliver a comprehensive
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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at the interface between stochastic modelling, signal processing and data science. Ultimately, the project will develop key indices that can be used to assess the health of the soil ecosystem. Such indices
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the interpretability of these models can be enhanced to support clinical decision-making. This project will leverage the complementary expertise of both supervisory teams in EEG signal processing, graph deep learning
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and Electronic Engineering Research Program and Control and Power Group, then indicate Dr. Elina Spyrou as a potential supervisor when making the application. The application should include a cover
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engineered mouse models for the depletion of different CAF populations, in vitro three-dimensional pancreatic tumour organoid/fibroblast co-culture models, CRISPR-based technologies, bulk and single-cell RNA