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an exceptional opportunity to conduct cutting-edge research at the intersection of machine learning, healthcare, and computational modelling, contributing to real-world clinical impact. What is offered
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co-supervised by both academic and industry experts, gaining valuable skills at the interface of hydrogeology, environmental engineering, and computational modeling. Research Objectives (1
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through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing
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university tuition fees. How to Apply: All applications should be made online . Under ‘Campus’, please select ‘Loughborough’ and select ‘Mechanical and Manufacturing Engineering’ under ‘Programme’. Please
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Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
at £1.2million project on Sleep and Mental Health. Dr Dominique Makowski with expertise in psychophysiology and computational neuropsychology. Dr Sean Figgins with a background and expertise in Sports Science, and
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benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions
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are part of the programme. The research is funded by the Centre of Propulsion and Thermal Engineering at Cranfield University. The work will be conducted at the Cranfield icing wind tunnel (IWT) based
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://www.bris.ac.uk/pg-howtoapply . Please select Mechanical Engineering (PhD) on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections
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background, we welcome applicants from other relevant disciplines, including psychology, sociology, criminology, law, and computer science. This PhD studentship is fully funded for up to 3.5 years with a tax