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protocols, and test hypotheses and analyse scientific data. You will be expected to contribute ideas for new research projects, develop ideas for generating research income, present detailed research
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successful in this role, you will hold (or be close to completing) a PhD/DPhil in machine learning, artificial intelligence, computer science, epidemiology, health data science, or a related quantitative
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of research investigating cancer risk and prevention. The appointee will work closely with Professor Ruth Travis, Dr Karl Smith-Byrne and other members of the research team, using large-scale epidemiological
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and spatial analysis techniques to large-scale spatial transcriptomics and imaging datasets, using tools such as MuSpAn to identify spatial biomarkers and uncover the biological mechanisms driving
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Patient Advisory Groups (PAGs), conducting qualitative interviews, running focus groups, designing and executing large-scale international surveys with quantitative data analysis, and collaborating
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FTE role supporting the international FEVER II study. C-GULL is a large contemporary birth cohort following up to 3-4,000 infants. Nested within C-GULL, HBHF is investigating early predictors of anxiety
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://aria.org.uk/opportunity-spaces/resilient-climate-and-ecosystems/accelerated-adaptation for more information on ARIA and this programme). The project is a collaboration between groups at the Universities
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, biomonitoring, and toxicity data. Key responsibilities: Lead UCAM's contribution to Task 5.2, including modelling of respiratory deposition of indoor particulate matter and estimation of exposure to aerosol-bound
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Neurodevelopment. You will develop, implement, and apply computational pipelines to analyse large-scale genomic datasets generated through Perturb-seq and other functional genomics approaches. You will use state
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for candidates to have the following skills and experience: Essential criteria 1. PhD (awarded or close to completion), or equivalent experience in human-computer interaction, AI or similar 2. Expertise