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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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responsibilities will include: Pre-registering data analysis plans; Leading and conducting advanced statistical analyses (e.g., twin/family designs, genomic and epidemiological methods, longitudinal modelling
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of areas. You will join the ATLAS group in the Particle Physics Research Centre, working within our L1Calo team, making leading contributions to the ATLAS calorimeter trigger upgrade for the high
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collaborate with bioinformaticians, experimentalists and clinicians. About You Essential requirements for this post include a PhD in a relevant biological or computational subject and background in
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to their own research interests. About You Candidates should have a PhD in a relevant discipline or will have obtained it by commencement of the position. Candidates should have some experience in multi
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develop, synthesise and characterise materials for this project. About You The post is suited to a PhD graduate with a background in materials chemistry or a related discipline. If you have a vivid
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and leading journals, and to undergo additional methods training. About You Educated to doctoral level in political science or a cognate discipline, you will be proficient in quantitative research
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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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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
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of those with and at risk of cancer through innovative research in the laboratory, in patients and in populations. BCI is internationally renowned in many areas of cancer research, and it combines ground