37 data-"https:"-"https:"-"https:"-"https:"-"https:"-"IFM" PhD positions at University of Nottingham
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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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, self-starter, PhD student to run the follow up questionnaires and analyse the data. This offers an exceptional research opportunity to investigate the contribution of lifestyle factors, particularly
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data-driven methods to develop an inverse design framework for manufacturing systems. Together, we will advance the capability to design manufacturing systems that embed reliability, resilience
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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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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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Studentship Information Supervisor: Vinay Shukla Subject Area: Plant & Crop Science Research Title: Root oxygen dynamics and development Research Description: The student will be part of a
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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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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