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neurophysiological and neuro-immune profiling of the impaired skin barrier and maladaptive neuronal responses underlying pain in epidermolysis bullosa. About You The candidate will have a PhD in the field
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-led by Queen Mary University of London. PharosAI is set to revolutionise AI-powered cancer care, accelerating the development of breakthrough therapies, advancing clinical applications, and improving
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fellow position within the William Harvey Research Institute at Bart’s and The London Medical School, Queen Mary University of London (QMUL). The post-holder will work on projects including the PinG study
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partners at NHS England and Nuffield Health. About You You will have a PHD (or close to completion) or experience at a comparable level in a relevant subject area. You will have experience of working with
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machine learning under real life constraints of clinical integration/validation and healthcare regulatory translation/commercialisation. The position is part of the project `Integrated autofluorescence
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-led by Queen Mary University of London. PharosAI is set to revolutionise AI-powered cancer care, accelerating the development of breakthrough therapies, advancing clinical applications, and improving
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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order to gain novel understanding of the molecular mechanisms underlying disease. About You You will have a PhD (or equivalent qualification) in computer/statistics/data science or similar field. You will
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degree, who hold an ACVECC Diploma. A background in research work in one of the College’s areas of special interest or hold a PhD, although desirable, are not essential. We offer a generous reward package
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PhD (or close to completion) or research qualification/experience equivalent to PhD level in the relevant subject area for the research programme; with a productive track record and have experience