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is 2:1. Degree in psychology, public health, epidemiology or other health-related discipline. Mode of study: Full-time Start date: 1 October 2026 Additional Funding Information This project is fully
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the ergogenic aid. Further information: Applicants should have at least a 2:1 in a relevant degree (for example but not limited to Sport Science/Medicine/Rehab, Public Health, Medicine), and ideally a relevant
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training will be provided. We particularly welcome applicants who are excited about integrating ecological understanding with data-driven methods. There is flexibility to tailor the research to your
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desirable. Entry requirements At least UK equivalence Bachelors (Honours) 2:1 or UK equivalence Masters degree. Mode of study Full-time Start date 1 October 2026 Additional Funding Information This project is
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and partner urban sites, the successful candidate will collect and analyse real-world environmental data to evaluate how vegetation interacts with the built environment. You will be supported by a
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and in-depth information about their vision. This could lead to a paradigm shift for monitoring vision in patients with MS – enabling earlier and more reliable detection of vision-related manifestations
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and experimental data, the student will develop predictive models of strand displacement reactions in non-ideal settings, in collaboration with the other students within BIOHYBRITE. These areas include
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for fuel system applications. While these methods provide a wealth of knowledge and information, they remain impractical for industrial use. Therefore, AI modelling techniques will be harnessed to develop
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computer simulations by developing fundamentally innovative and advanced protection strategies. To enhance the reliability and safety of low-voltage networks with a high penetration of power-electronic
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fees. See UKCISA for further information. Starting in October 2026. Later start dates may be possible, please contact Dr Lucia Florescu once the deadline passes. You will need to meet the minimum entry