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materials science expert, combining cutting-edge characterisation with real-world industrial impact. At the University of Manchester, working in partnership with the Royce Institute and Cummins, you will
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. Essential: A 2:1 undergraduate degree or a Master’s degree in Physics, Applied Physics, Mathematical Sciences, computer science, vision science or a closely related subject from a recognised institution. A
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of Education, Environment and Development: 19 January 2026 School of Social Sciences: 1 December 2025 Deferral information Offers of funding are not deferrable. If you cannot start your programme by the date
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throughout, ensuring research questions are grounded in real farming challenges and that outputs reach the people who need them. What You Will Do Working across agronomy, soil science, and microbial ecology
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-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty
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Background The nuclear industry is increasingly seeking to deploy robotic and autonomous systems were possible to reduce worker exposure to hazardous environments, improve productivity and enhance operational resilience. Whilst significant progress has been made in remote operations, a major...
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Specified use The awards are available on a competitive basis for candidates joining the PhD Accounting & Finance, PhD Business & Management or PhD Science, Technology & Innovation Policy programme at
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to participate in this collaborative research programme. They will be expected to contribute research to central datasets, and will be encouraged and supported to develop high-profile publications at the cutting
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Location: Mechanical and Aerospace Systems Research Group, Faculty of Engineering, University of Nottingham Funding: UK Home fees + tax-free stipend of up to £25,000 p.a. for 4 years Applications
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Funded PhD studentship in AI-assisted materials discovery at the UK National Epitaxy Facility School of Electrical and Electronic Engineering PhD Research Project Competition Funded UK Students