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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
We are seeking an exceptional candidate for a fully funded PhD studentship investigating the role of sleep and circadian rhythms in elite athletic performance, co-funded by Brighton & Hove Albion
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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increase healthcare access. Further, such technologies can facilitate remote training monitoring and performance enhancement for athletes. Developing accurate, low-cost, comfortable technologies
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Verification Tools: Develop AI algorithms that automate the verification process, ensuring systems meet required safety and performance standards. Health Monitoring Algorithms: Implement AI-based monitoring
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full postgraduate research programme Please note that existing postgraduate research students cannot be considered for this funding. Tenable period 3.5 years full-time or 7 years part-time. Continuation
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Specified use +4 - covering a full postgraduate research programme Please note that existing postgraduate research students cannot be considered for this funding. Tenable period 4 years full-time or 8 years
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of health and wellbeing in middle aged women. The successful candidate will join a thriving research department examining how nutrition can improve health, wellbeing, and exercise performance. As this project
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requirements for your preferred programme, in addition to those specified by RADMA. Nationality restrictions This funding is available to all nationalities. Other eligibility criteria This award is available
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-edge biological modelling to understand exactly how IIDs spread in nurseries. The project aims to develop improved intervention guidelines to prevent high mortality IIDs, considering what’s realistic and
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performance, with between 2% and 12% of the energy intake by dairy cows being lost as CH4 (McDonald et al., 2021). Consequently, reducing CH4 production improves feed use efficiency by dairy cows and is