52 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" PhD positions at University of Nottingham
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Studentship Information Supervisor: Professor Ian Fisk Secondary Supervisor: Dr Vincenzo di Bari, Dr Louise Hewson, Mui Lim Subject Area: Food Science Research Title: Sodium Reduction in Coated
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trigger redesigns across multiple groups. The challenge is compounded by the fact that each discipline uses different data models and representations, making system-level interdependencies difficult
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in a relevant subject – Biomedical Sciences, Biomedical/Information Engineering, Computer Science, Analytical Bioscience, Physics or related disciplines. Prior experience with medical imaging
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Data is more valuable than oil, so it has been said. Quantum computing offers new unusual datasets thereby presenting new opportunities for AI approaches. Quantum computing is raising the prospect
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subject – Biomedical Sciences, Biomedical/Information Engineering, Computer Science, Analytical Bioscience, Physics or related disciplines. Prior experience with medical imaging, particularly MRI, medical
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strategy to improve the turbulence detection and quantification. The flow turbulence and velocity in a vascular flow phantom will be measured by Particle Image Velocimetry (PIV), against which MRI data will
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support a more controlled, data-informed manufacturing environment and improve structural performance across the full lifecycle of high-value engineered components. Aim The student will have opportunities
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in advanced experimental techniques, data analysis, and interdisciplinary problem solving at the interface of physics, materials science, and device-relevant functionality. Outcomes will include high
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that deliver healthier indoor environments, lower carbon emissions, and long-term building performance. By integrating Passive House and EnerPHit principles with real building data, the research will support the
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the Faculty of Engineering, plus those housed in Plant Biosciences at the Sutton Bonnington campus. Data sets will be generated using simulated and experimental data and these will be used to train networks