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PhD Studentship Aircraft Electrical Power System Stability This exciting opportunity is based within the Power Electronics and Machines Centre (PEMC) Research Group at Faculty of Engineering which
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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the Manufacturing Technology Centre (MTC). It is based within the Advanced Manufacturing Technology Research Group (AMTG) at the Faculty of Engineering, University of Nottingham, which amongst its wide research
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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engineering. Expertise in numerical electrical machine design tools (Ansys, JMAG, .etc) as well as corresponding scripting skills are desirable. Experience in electrical machine prototype development would be
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engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine prototype development would be advantageous. Eligibility and Application
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-assignment checks. If the position you are applying for is ‘exempt’ from the Rehabilitation of Offenders Act 1974 you will be asked to confirm both spent and unspent convictions at the point of offer. Examples
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leverage advanced bespoke continuum robotic systems to demonstrate the feasibility of applying the proposed coatings can be deployed in-situ. Ultimately, this work bridges the gap between the theory
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power systems. You will join a large group of postgraduate students in the Faculty of Engineering, working on many aspects of solar energy and zero carbon technologies. The team of potential PhD
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of chemical data. Key Responsibilities: Utilise high data-density reaction/bioanalysis techniques, including high-throughput experimentation, to inform and enhance drug optimisation. Employ machine learning