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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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conferences. Candidate requirements: Due to funding restrictions, the position is only available for UK candidates 1st or 2:1 academic qualification in Engineering or Physical Sciences or a related discipline
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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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Century through foundational and applied AI research on a cohort basis. The training and supervision will be delivered by a team of outstanding scholars from different disciplines cutting across Arts
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design, construction, renewal, engineering, technology, and research and development. Takenaka is committed to excellence and sustainability in the construction industry. Takenaka is working in
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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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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: Rolls-Royce Sponsored PhD Scholarship – Micromechanics and In-Depth Materials Analysis of Advanced Aerospace Materials Upon the Manufacturing Process Engineering Applications
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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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, refractive index measurement tools, and near-field imaging systems. The ideal candidate will have: A first or upper second-class honours or Master's degree in Physics, Applied Physics, Electrical and