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Application deadline: All year round Research theme: Systems and Control How to apply: uom.link/pgr-apply-2425 This 3.5 year PhD project is funded by The School of Engineering and is available
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of interventions designed to meet the development needs of coaches. The project will be led by Professor Andy Smith, Director of the Centre for Mental Health, Sport and Physical Activity Research and Head of
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
Overview: Cranfield University invites applications for a fully funded 3-year PhD, supported by the EPSRC DTP and Rolls-Royce. This studentship covers tuition, a tax-free stipend, funding
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industries, including transportation, consumer electronics, and industrial automation. This PhD project focuses on the design and optimization of intelligent systems with an emphasis on energy efficiency and
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Application deadline: 15/08/2025 Research theme: Computer Science No. of positions: 1 Eligible for: UK This 4-year PhD project will be funded by DLA studentship and is open to UK students
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The project: We invite applications for a fully funded PhD studentship in the Solid Mechanics Group at the University of Bristol to work on the predictive modeling of hydrogen-induced damage in
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Duration of Award if full time preferred*: 4 years 1st Supervisor: Dr Tao Lyu 2nd Supervisor: Prof Bruce Jefferson This exciting fully funded PhD, with an enhanced stipend of £25,726 per annum
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Project details: Various dietary supplements have been shown to possess bioactive effects that could enhance health and wellbeing. However, few studies have examined longer-term intake of different supplements combinations on relevant markers. Our project aims to examine effects of dietary...
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colleagues at Public Health to evaluate the development of a Mental Wellbeing approach that is designed with and delivered by the Voluntary, Community, Faith and Social Enterprise Sector. The learning from
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems