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duration: October 2025, for 3.5 years. Candidates must possess or expect to obtain, a 2:1 or first-class degree in Engineering, Physics, Chemistry, Materials Science, or related physical sciences discipline
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, electrochemical characterisation, or related fields. A strong degree (first or high upper second) in Materials Science, Mechanical Engineering, Chemical Engineering, Physics, or a related discipline is preferred
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participate in the dissemination of findings through publications and conferences. Qualifications: Completed or nearing completion of a Master's degree in Medicinal Chemistry, Chemical Engineering, or a related
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national depending on suitability. Interested candidates in the areas of Engineering, Physics, Biology or Medicine please contact fernando.perez-cota@nottingham.ac.uk or richard.lea@nottingham.ac.uk by
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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, Engineering, Medicine and Health Sciences, Science and Social Sciences. The University of Nottingham Faculty of Science AI DTC offers the opportunity to: • Choose from a wide choice of AI-related
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based