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high-priority condition as new disease-modifying therapies are developed. This PhD tackles a key diagnostic bottleneck in ADTKD-MUC1 and integrates precision genomic medicine into routine kidney care
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2025. Encouraged by the continuing success of modern machine learning (ML) techniques, researchers have become ambitious to develop ML solutions for challenging science and engineering problems with
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to compensate for such aberrations, significantly enhancing image quality. Adaptive requires knowledge of the wavefront to be corrected. Our team has been developing a machine-learning approach to wavefront
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programmes in the first three years, of which will be followed by committing to an industrial placement in the fourth year of this doctoral programme. Supervisors: Entry requirements: Essential: A first or
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, this is only available to those eligible for UK fees. All applications should be made online via the above ‘Apply’ button. Under Campus, please select ‘Loughborough’ and select Programme ‘Chemistry’ Please
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The transition from the traditional relative perspective in engineering design and product development (“Is design A better than design B?”) towards an absolute sustainability perspective (“Is the
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a
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This PhD project offers the opportunity to explore a rich and rapidly developing area of research where powerful mathematical ideas unlock exact solutions in quantum physics. Most physical systems
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This PhD project will develop next-generation grid-scale energy storage solutions integrated into HVDC (High Voltage Direct Current) systems at the University of Edinburgh, in partnership with UK