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desirable but learning can be completed during the PhD. Excellent communication and interpersonal skills to facilitate collaboration within interdisciplinary research teams. Application Process: To apply
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers the opportunity for the PhD student to lead the development of innovative simulation tools
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supercritical water systems to generate samples that will help optimise a process that will then be scaled into pilot and large scale pilot systems with partners in the consortium. Aim This project will focus
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between chemical and mechanical aspects of sperm cell biology remain largely unknown. In this project a successful candidate will learn, elasticity characterisation techniques, processing and evaluation
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of £3,000. Starting date will be preferably on 1st October 2025. Home students are strongly encouraged to apply. Please send your CV (including publications if apply) and transcripts to Dr Ke Li (ke.li2
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outstanding facilities and works in partnership with leading industrial partners. For further information or to apply, please send Dr Sanliang Ling (Email: Sanliang.Ling@nottingham.ac.uk ) a covering letter, CV
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to national and international conferences. Working as part of a team of experienced researchers including Dr Rachel Nicks (PI) and Prof Stephen Coombes (Co-I) and a post-doctoral researcher focussed
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rely on unsustainable materials and on carbon-intensive manufacturing processes. This is posing major environmental and ethical challenges. The project will motivate the PhD student to develop next
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integrated Masters, a BSc + MSc or a BSc with substantial research experience will be highly advantageous. Experience in computer programming will be essential. The studentship is open to home students only