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Field
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computer modelling (in silico), through robot driven testing of implanted knees (in vitro), to 3-dimensional X-ray imaging of moving patients (in vivo) with Machine Learning driven analysis, to deliver a
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on the development and pre-clinical assessment of both molecular and cellular immunotherapy products, using in vitro and in vivo platforms. You will process clinical samples, operate specialist laboratory equipment
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benefits across the healthcare supply chain. Candidate Profile: A PhD in a related field is highly desirable given the technical complexity and innovation. Skills/ experience required include: Essentialfor
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across the world and a wider group of stakeholders, you will lead the research on advanced image reconstruction techniques that jointly process multi-contrast MRI data to maximize image quality—leveraging
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Overview The Research and Innovation Associate will assist in the research and publication of two major books on the twentieth-century poet Elizabeth Bishop: a trade book of her picture postcards
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tissues • The development of computational methods ranging from image processing to machine learning to analyse, segment, model, and quantify large-scale time lapse datasets Main duties
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physiological data, as well as with prior experience in participant recruitment and/or experimental testing. They will hold a PhD in the field of machine learning and prediction/decision modelling or related
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high-throughput screening using genetic and imaging tools. Apply molecular and cellular assays to study inflammatory processes. Analyse integrative omics datasets using bioinformatics and machine
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Experience in genetics and cloning Experience with advanced bioinformatics tools. High ability to express yourself both orally and in writing. Computer literacy (MS-Office; Imaging Software). Basic experience
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Identifying novel regulators of colorectal cancer invasion School of Biosciences PhD Research Project Self Funded Dr Kyra Campbell Application Deadline: Applications accepted all year round Details