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respiratory, cardiovascular and psychiatric genomics but we welcome applications from other clinical areas. The group develops and applies statistical methods to enable genetic epidemiology studies, with
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.’ About you As the successful applicant, you will have a PhD in a relevant area (e.g. Biostatistics/Medical Statistics/Epidemiology) as well as experience in advanced statistical modelling techniques
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, mathematical biology, statistics, statistical mechanics, (stochastic) dynamical systems, mathematics of Planet Earth, Artificial Intelligence, data science, or other areas consistent with our existing strengths
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statistical methods to analyse large-scale genomic datasets and decipher evolutionary patterns. Perform wet-lab experiments aimed at validating cell-diversity. Collaborate with multidisciplinary teams
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statistical genetics methodologies, such as GWAS (Genome-Wide Association Studies) and PheWAS (Phenome-Wide Association Studies), is essential. Proficiency in statistical programming languages (e.g., R, Python
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across financial mathematics, economics, statistics, data science, mathematical modelling and risk management. You should have teaching experience in data science and/or actuarial science at Core
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Epidemiology, Medical Statistics, Health Data Sciences or other relevant quantitative disciplines and previous experience in environmental epidemiology for example air pollution, noise or chemical impacts
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situ hybridisation. You will also have sound statistical and bioinformatics knowledge, with ability to program in R. Alongside a technical and research background, you will also need to be able to work
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About the role The Department of Population Health Sciences is looking to appoint a Research Associate to develop statistical methods for disease mapping. In particular, this role will consist