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experimentation and finite-element modelling. Research themes would be flexible including green steel formability under the EPSRC ADAP‑EAF programme for automotive and packaging applications; or micromechanical
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, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform statistical analyses to assess stability and plasticity of multisensory
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visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
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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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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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early ‘prodromal’ stages) is yet to be established in large community settings. This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative
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inequality in health and social care, drawing on critical race and intersectionality frameworks, and work closely with postdoctoral researchers to support qualitative elements of the project, including ethics
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inequality in health and social care, drawing on critical race and intersectionality frameworks, and work closely with postdoctoral researchers to support qualitative elements of the project, including ethics
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propellant space propulsion systems. A significant limiting factor of hybrid propulsion systems is the continuous change in surface area of the propellant grain during the combustion process. This changing O/F
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collection and analysis such as interviews, discourse analysis, participatory workshops, coding, and content analysis. The postholder will also contribute to the new Race Equity in Care survey, including