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AI-electronic systems with applications in aerospace, healthcare, and beyond. As AI systems become increasingly integrated into critical applications, ensuring their security and trustworthiness is
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This 3.5 year PhD project is fully funded for home students; studentship is open to Home (UK) applicants only. The successful candidate will receive an annual tax free stipend, set at the UKRI rate
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orbital parameter extraction using image processing techniques. The ideal candidate should have a strong background in physics, engineering or a related field, as well as experience working with programming
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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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have a 1st class degree (BEng or MEng/MSc) in electrical/mechanical engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine
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. This project is part of an exciting new Doctoral Training Programme in Microbial Genomics for Health Protection in collaboration with the UK Health Security Agency (UKHSA). This is funded by NIHR as part of a
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, including mobility payments and family allowances where applicable https://marie-sklodowska-curie-actions.ec.europa.eu/actions/doctoral-networks . Salary is subject to local tax, employee and employer social
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applicants who wish to study for a PhD research degree in one of its Schools or Colleges Particular attention will be paid to applications aligned with one (or more) of our research strategic priorities
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, above. Select programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you
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Training Programme in Microbial Genomics for Health Protection in collaboration with the UK Health Security Agency (UKHSA). This is funded by NIHR as part of a Health Protection Unit in Public Health