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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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Open to UK students This 3.5-year PhD project is fully funded for home students or EU students with settled status. Tuition fees will be paid and the successful candidate will receive an annual tax
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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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, 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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disturbances. This programme of doctoral work will investigate the prevalence of iron deficiency/ iron deficiency anaemia in high performing athletes and assess the effectiveness of a novel oral iron supplement
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health, and intelligent operations. It is particularly suited to candidates with academic backgrounds in Industrial Engineering, Aerospace Engineering, Management Science, Operations Research, Transport
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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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Discipline: Engineering & Technology, Materials Science, Mechanical Engineering Qualification: Doctor of Philosophy in Engineering (PhD) This collaborative project between Jaguar Land Rover (JLR
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Annual tax-free stipend of £22,780/year for 4 years, full coverage of tuition fees for UK/Home Students, plus training/travel funds Placed On: We invite applications for a fully funded PhD research
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-periodic structures, we can precisely control the interaction of radiation with matter, potentially achieving unprecedented timing resolution (sub-70ps) and significantly enhancing signal detection. This PhD