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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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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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role: This post, funded by an ERC Consolidator Grant (DISCO), focuses on the dynamic behaviour of ferroelectric domain walls using advanced cryogenic and electrically biased 4D scanning transmission
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of the start date) Salary: Grade 5: £32,546 - £35,116 Grade 7*: £35,116 - £45,413 The funds for these posts are available until 6 months from commencement in post. This is a full-time position. Location
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Modelling post combustion amine CO2 capture plant School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof Mohamed Pourkashanian, Prof Lin Ma, Dr Kevin Hughes
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Health economic evaluation of community acquired pneumonia in the UK Pneumonia is a common illness that results in over 100,000 hospital admissions per year in the UK. Following hospital treatment
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable
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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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THR demand in younger patients expected to increase fivefold by 2030, revision surgeries will also rise. To improve implant positioning, image-guided navigation is increasingly used in complex THR
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. The initiating secondary genetic changes causing overt clinical disease that progresses to metastasis remains unknown. Metastasis is thought to be independent to tumorigenesis. Metastasis is a highly complex