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, is needed. The project will motivate the PhD student to develop next generation electric motors with advanced CNT windings for electric vehicle traction and aerospace propulsion, featuring improved
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We are looking for an outstanding PhD student with either strong background in computational modelling or significant experience of laboratory work, who is keen to work at the interface between
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submitted your formal application is Sunday 19th April 2026. Start date is 1st October 2026. Annual tax-free stipend based on the UKRI rate (£21,805 for 2026/27) plus fully-funded PhD tuition fees for the 3.5
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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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struggles to reflect real-world situations where people actually experience the products. This PhD aims to change that by using immersive technologies such as virtual reality (VR), mixed reality, and
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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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to the inaccuracy of turbulence measurements. These are the main issues that the proposed PhD study will address. The research work will be conducted by using a vascular flow phantom, guiding the MRI scanning
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Zero technologies such as electrified transport, power electronics and energy conversion. Vision We are seeking a highly motivated and ambitious PhD researcher who is excited by fundamental materials
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of Sport, Exercise, and Nutrition Education – kimberley.edwards@nottingham.ac.uk This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: Athletes, coaches
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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