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Application deadline: 01/08/2025 Research theme: Turbulence, Fluid Mechanics, Offshore Conditions, Renewable Energy, Hydrodynamics, Experiments This 3.5 year PhD is fully funded for applicants from
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, adaptive control strategies, and hybrid energy storage solutions to address key challenges in self-powered systems under dynamic environmental conditions by: Develop machine learning or heuristic-based
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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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Research Studentship in DPhil in Engineering Science Industrial Doctoral Landscape Award (IDLA) in Gas Turbine Heat Management. 4 year D.Phil. studentship Project: DPhil in Engineering Science Industrial Doctoral Landscape Award (IDLA) in Gas Turbine Heat Management. Supervisors: Prof Peter...
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About the Project WE ARE RECRUITING four PhD students to start in October 2025. Each 4-year studentship is generously funded with an enhanced stipend, all tuition fees covered, and research support
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Cranfield University and Magdrive, offer a fully funded PhD position under the umbrella of the R2T2 consortium to study the optimisation of their thruster for a kick stage. R2T2 is a UKSA-funded
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specific drug resistance and pathogenesis mutations. The project will combine classical microbial genomics with machine learning and AI analysis approaches to create the most in depth population analysis
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an independent impact assessment of potential climate interventions in the Arctic marine environment through laboratory experiments and computer modelling. The team will develop physical, climate and ecosystem
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We are delighted to announce a 3-year PhD scholarship in French or Francophone Studies at the University of Sheffield. The Dorothy Tingle Bequest Scholarship has an annual value of £12,000 towards
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energy; thereby minimising farming’s environmental impact. AI machine learning offers a new expedient method of developing control systems for tasks that would be difficult to manage using classical