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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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providing a structured, semantic framework that enhances knowledge sharing and data reuse across different platforms and systems. Project Aim This PhD will develop an ontology-based methodology to improve
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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