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Solutions, you will apply your methods in detailed simulation studies using Imperial’s high-performance computing facilities, assessing performance in realistic scenarios. You will regularly present your
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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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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
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such as transportation and heating. These two transformations create a need for sophisticated planning methods and processes that result in actionable plans by proactively considering high-impact forces
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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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for impact by addressing computational problems and real-world healthcare challenges. The researcher will be responsible for developing and implementing new approaches, testing and evaluating methods on real
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The role The post is part of the Wellcome Discovery Award research programme “Collective Action for Race Equity in Health and Social Care”, which aims to address and dismantle structural factors
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research programme, titled Collective Action for Race Equity in Health and Social Care (CARE-HSC), aims to address and dismantle structural factors that perpetuate racial discrimination and harassment within