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To undertake research on the evolution of prokaryotic pangenomes using machine learning and AI approaches. The work will involve the analysis of large prokaryotic genome datasets, the development
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epidemiology, data science, and policy to produce high-quality, policy-relevant evidence with real-world impact. You should have a PhD (or near completion) in public health, epidemiology, data science, applied
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prison sites, recruitment and data collection, and complex data analysis. You should have a PhD (or near to completion) and an Undergraduate degree in psychology or a relevant discipline. You will have
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activities, and will be supported to develop their own independent research trajectories and career pathways throughout the project with access to bespoke training and conference budgets. You should have a PhD
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the growth of mastitis-causing pathogens. Performing on-farm environmental sampling of dairy cubicles and teat-end swabbing to gather real-world data. Evaluating the relationship between cubicle hygiene
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to meetings with industrial collaborators if required ¿ Engage with your own personal development opportunities. You should have a degree in Chemistry and a PhD in polymer chemistry. All applicants must
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environment, and benefit from diverse project team skill and expertise. The successful candidate should have a PhD in cartilage, stem cell or protease biology (or a related discipline). Expertise in mammalian
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. You will also contribute to publications and grant applications. Training will be provided as needed. You should have a PhD degree in a biomedical science-related subject and significant experience in
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tissues. The data generated from this proof-of-concept project will be used to support follow-on research and translational grants. To ensure clinical relevance, you will also collaborate with patients
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should have a PhD degree in Biochemistry, Biomedical Science, Biological Sciences, Omics science, Microbiology or a related discipline and experience of applying mass spectrometry in human signalling