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, curious individual to join an exciting PhD. This opportunity is generously funded by John Crane Ltd, a world-renowned engineering technology leader. Why This PhD? Impact Clean Energy's Future: Develop next
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, with a slightly higher teaching requirement alongside the PhD studies and would particularly suit someone with an interest in future education as well as research, such as academia. Supervisors:Professor
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The primary objective of this project is to establish the evidence base on professional cycling road ‘racing’ trends and the critical tactical moments that determine how races are won. This evidence will inform future race strategy and live race tactics. Multiple factors influence the strategy...
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This PhD focuses on the development of a novel approach to measuring the traction behaviour of artificial turf, supported by FieldTurf, a global leader in the production of artificial turf for sport
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, Aerospace and Civil Engineering at the University of Sheffield, and embark on a transformative PhD project funded by John Crane Ltd, a global leader in engineering technology. What’s the Project About
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www.ucl.ac.uk/lbs . About you We are looking for a Black British student with PhD research interests within the broad themes of media, culture, politics, restorative justice and reparations for the Transatlantic
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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Please quote reference: Quantum Computing at The School of Physical Sciences Duration: 3 years and 6 months. We are currently recruiting for the following full-time, fully funded PhD studentship
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) Applications are invited for a three-year PhD studentship. The studentship will start on1st Jan, 2026. Project Description Glioblastoma (GBM) is the most aggressive and treatment-resistant form of brain cancer
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust