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Field
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machine learning and AI methods to develop clinical decision support systems for high-flow nasal cannula therapy. The project: Concerns around the possible negative consequences of delayed escalation
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, they are inherently fragile and often lost after repeated washing. Drawing inspiration from contemporary organic chemistry, this project will explore methods to permanently restore structural integrity by covalently
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repeated washing. Drawing inspiration from contemporary organic chemistry, this project will explore methods to permanently restore structural integrity by covalently repairing damaged bonds within hair
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the ARIA (UK Advanced Research + Invention Agency) Robot Dexterity Programme, and is a collaboration with University College London, INESC Microssistemas e Nanotecnologias (Portugal) and Universidad de
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AstraZeneca and Newcastle University , will develop predictive models for pharmaceutical manufacturing and provide access to industrial data and high-performance computing facilities. You will gain expertise
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computational methods to extract infection dynamics from individual cells Integrating experimental observations with mathematical and statistical models of phage-host interactions. The successful applicant will
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Additive manufacturing offers significant opportunities to produce complex, lightweight components that would be difficult to manufacture using conventional methods. One important application is the
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major £10 million national research programme bringing together leading experts in cancer epidemiology, biostatistics, artificial intelligence, and health data science. THE PROJECT: Early cancer diagnosis
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formulations & application methods, and comprehensive performance tests, including water contact angle measurements, breathability tests, absorption tests, biological resistance assays, and environmental chamber
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part of the NIHR Mental Health Research Group's programme of research exploring whole-university approaches to mental health. While universities have invested considerable effort into improving student