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Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives for aviation use
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Grand Tours, one-day races (monuments and semi-classics), and select World Tour 1-week stage races. The data sources will include video and previous race commentary to ‘code’ key events in races that help
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PhD Application". Emails should arrive no later than 1 September 2025. Applications may close early if the position is filled before this date. Please note that any offer of funding will be conditional
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How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded for home students or EU students with settled status; the successful candidate will receive a tax-free stipend set at
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Location: UK Other Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives
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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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Ovarian cancer is the deadliest of all gynaecological cancers (>2000 deaths/year, UK). It is described as a silent killer as most diagnoses occur after it has spread to the peritoneal cavity (metastasis). It is known that peritoneal cells contribute to the growth of metastatic tumours....
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performed annually in the UK. However, about 20% require revision within 15 years due to complications like implant loosening, dislocation, and fractures caused by suboptimal implant positioning. With primary
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submitted via the PhD Chemistry programme page, by clicking on 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
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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