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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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treatments. To date, there are few techniques that integrate AI and digital twins to improve patient outcomes. Your Role In this project, you will develop new methods that combine AI and digital twins
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treatments. To date, there are few techniques that integrate AI and digital twins to improve patient outcomes. Your Role In this project, you will develop new methods that combine AI and digital twins
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elements offers moderate strength and relatively high productivity compared to its highly alloyed counterparts. However, automotive aluminium alloys are susceptible to natural ageing at room temperature
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defects and the resultant fatigue life of metal additive manufactured samples. The project is part of a Villum Investigator grant titled “Microstructural engineering of additive manufactured metals
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annotations are scarce or unreliable. Recently developed unsupervised learning methods allow to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them
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, covering all cardiac conditions. This makes them unsuitable for identifying rare or complex cases, where annotations are scarce or unreliable. Recently developed unsupervised learning methods allow
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experience in this clinical field is not essential. We welcome applications from early career researchers with relevant expertise in a wide range of quantitative or qualitative methods (e.g. epidemiology
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of adding alloying elements and removing unwanted alloying elements to meet the customer’s specifications. Impurities are one of the biggest challenges for Al recycling. This project is aiming to develop
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present with neurodevelopmental deficits associated with Autism Spectrum Disorder and hyperphagia, and in healthy controls. We will be using a range of methods, including behavioural phenotyping, cognitive