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candidates with: • Relevant subject matter experience at required level (e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) • Willingness to adapt and work across different
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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites Research Groups at the Faculty of Engineering, which conduct cutting-edge research into electric...
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systems of differential equations. The resulting models will be analysed with analytical tools from applied mathematics and numerical studies in the Julia programming language. The successful candidate
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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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benign reagents. Applicants should have, or expected to achieve, at least a 2:1 Honours degree (or equivalent if from other countries) in Chemistry or Mathematics or a related subject. A MChem/MSc-4-year
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salary) for 3 years An additional £2,000 per annum for consumables and travel Requirements The candidate should have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics
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, mathematics, or related disciplines. Skills in numerical tools and programming are desirable. Any experience in engineering design or manufacturing would be advantageous. Eligibility and Application Due
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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: Classical Music’s Colonial History (1750-1900). The candidate will benefit from working as part of a lively interdisciplinary team, but the PhD studentship will also be a discrete project that the candidate
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Engineering Research Group) Aim: Develop a mathematical model for analysing reliability and efficiency of medical processes Background Adverse events and preventable failures in healthcare services represent a