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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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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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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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an attractive annual tax-free stipend; Join a multidisciplinary cohort to benefit from peer-to-peer learning and transferable skills development. For full information about the programme, the research projects
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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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to architectural design, human-building interaction, digitally-driven adaptive architecture, personal data, mental health and wellbeing, and theories of embodiment. What is the funding for: full fees and a monthly
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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
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for candidates who can demonstrate strong research potential. Suitable backgrounds include, but are not limited to: Human Factors Law (particularly law and technology, medical law, or data governance) Psychology