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exome/genome sequence data in both clinical genetic studies and/or large-scale population studies, such as the UK Biobank Study. Applicants must have a PhD in genetic epidemiology, statistical genetics
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are enthusiastic about investigating and engineering real-world solutions to pressing data-centric problems and to do so in a way that pulls on rigorous Bayesian statistics and scalable computational resources
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are enthusiastic about investigating and engineering real-world solutions to pressing data-centric problems and to do so in a way that pulls on rigorous Bayesian statistics and scalable computational resources
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reports, as well as some limited administrative duties and supervision of more junior researchers and students. The project would suit candidates with a PhD in neuroimaging, medical imaging, biomedical
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approaches to unravel causal pathways in the development/progression of immune-mediated disease. You will hold a PhD and demonstrate enthusiasm to develop experience in statistical genetics and data science
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contract. About you: Essential criteria 1. PhD in a relevant field (e.g., neuroscience, neuroimaging, engineering, mathematics, statistics, computer science, physics) 2. Substantial research
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computational background and significant (>5 years) experience of using bioinformatics and statistical approaches to analyse and interpret whole transcriptome data generated from RNA sequencing and integrate
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the knowledge and ability to teach across a range of topics in actuarial science, in particular the Core Statistics and Core Modelling subjects (CS1, CS2, CM1, CM2). About the School/Department
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a diverse team and able to perform effectively under multiple demands. Applicants should be educated to PhD level in a relevant discipline, have experience of working with R, multilevel modelling, and
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Qualifications • Postgraduate qualification relevant to applied health and care research • PhD in social care research, health research or related discipline e.g. health services research, health economics