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, process stability, and the downstream consolidation and performance of remanufactured composites. This fully-funded PhD project fits within a wider research programme with industrial partners and an
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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
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the NIHR as part of EPR-HPRU between the University of Birmingham and UKHSA. In addition to the extensive training offered to all PhD students at UoB, the student will receive training and opportunities
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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via the PhD Chemistry programme page, by clicking the 'Apply' button, above. In place of a research proposal, you should upload a document stating the title of the project that you wish to apply for and
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Funding Source: Warwick Industrial Fellowship (WIF) in partnership with Hydrograph Eligibility: UK only Supervisors: Professor Tony McNally, Dr Fengzai Tang Supporting Company: Hydrograph (see Home - HydroGraph ) Start date: 6th October 2025 Project Description – The aim is to develop a...
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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and establish their potential remain to be answered, both in terms of enabling technologies for distributed sensing and the techniques that exploit it. The focus of the PhD project is to improve our
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2025 Reference: RD-PHD-01-LS-MH-25 Project Title: The cost of silage production: measuring the carbon footprint of silage Primary supervisor: Prof. Liam Sinclair Co supervisors: Dr Kate Le Cocq, Dr