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Rolls-Royce and EPSRC funded PhD - Experimental and numerical studies into the wear of articulating spline couplings for aeroengine applications Applications are invited for an EPSRC Industrial
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Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through
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Background UK applicants are invited to undertake a 3-4 year, fully-funded PhD studentship (fees and enhanced stipend) within the Centre of Excellence in Coatings and Surface Engineering (CE-CSE
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contributor, yet sodium plays a critical functional role in batter systems, influencing flavour delivery, texture, processing robustness, and consumer enjoyment. This fully funded PhD studentship will tackle
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EngD Studentship in the EPSRC Centre in Doctoral Training (CDT) in Innovation for Sustainable Composites Engineering This opportunity adds to the portfolio of projects within the new CDT for Innovation for Sustainable Composites Engineering launched in...
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PhD Project: 3D-Printed Drug Delivery “Microbots” for Personalised Healthcare Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing
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The Faculty of Science AI Doctoral Training Centre (AI DTC ) invites applications from Home students for fully-funded PhD studentships to carry out multidisciplinary research in the world
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target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing on the glioblastoma infiltrative
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This project will develop and apply spin-polarised scanning probe microscopy to image, understand, and control magnetic order at the atomic scale in unconventional magnetic materials. Using low-temperature scanning tunnelling microscopy (STM) and atomic force microscopy (AFM), the work will...
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at the tumour margin represent a key target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing