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computer literacy, good inter-personal communications skills. Desirable skills: A Master in Health Economics with experience in cost effective analyses. Funding notes The three year studentship covers UK
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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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candidates with: • Relevant subject matter experience at required level (e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) • Willingness to adapt and work across different
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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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(e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) Willingness to adapt and work across different disciplines Ability to work independently and cooperatively Commitment
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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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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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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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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