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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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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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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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Proteins are key biomarkers, indicative of normal biological or pathogenic processes and responses to intervention. Identification and quantification of such molecules in biological fluids is
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such as transportation and heating. These two transformations create a need for sophisticated planning methods and processes that result in actionable plans by proactively considering high-impact forces
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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/learning based techniques in the areas of robotics, or autonomous systems, • interested in autonomous systems and signal processing, • Keen to work with equipment and embedded