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Research Studentship in DPhil in Engineering Science Industrial Doctoral Landscape Award (IDLA) in Gas Turbine Heat Management. 4 year D.Phil. studentship Project: DPhil in Engineering Science
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for understanding natural magmatic processes on earth & other planetary bodies. Neutron diffraction is a powerful technique for studying the atomic scale structure of these materials, but the current technology to
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£20,780 per year, and includes a 3-month fusion engineering CDT training programme as part of the 2026 Cohort. This project is co-supervised by Dr Chris Hardie from UKAEA. The UoB Materials for eXtremes
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-based structural integrity model, validated using synchrotron X-ray microtomography and phase contrast imaging, to predict the lifetime of UK’s advanced gas-cooled reactors fuel cladding in storage
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Sodium-ion batteries are rapidly emerging as a powerful alternative to lithium-ion systems—offering significant advantages in cost, sustainability, and safety. To unlock their full potential, advanced gel polymer electrolytes (GPEs) are needed to boost energy density and reliability. This PhD...
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The aim of this project is to analyse the effect of hydrogen and Low Carbon Intensity (LCI) fuels on degradation of surfaces exposed to such harsh environments and, subsequently, structural
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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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Area Engineering Location UK Other Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and
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Boreal forest recovery after clear-cut: We are looking for a highly motivated PhD student to collect data on and model hydro(geo)logy and greenhouse gas exchanges of boreal forests after the disturbance. Boreal forests constitute the second largest forest biome after the tropical rainforest,...
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early