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analytical methods for the analysis of linked data from electronic health records and genomic or molecular sources. Strong statistical skills (e.g. proficiency in R or Stata), along with excellent writing
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward
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, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful
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, biomedical sciences, or a related discipline. A relevant Master's degree is desirable but not essential. Experience in quantitative statistical methods is essential, and autism research experience would be
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language processing (NLP), large language models (LLMs), machine learning (ML), and data visualization. The candidate will leverage their expertise in AI, statistics, and programming to design, develop, and evaluate
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range (but not all) of these: *Carrying out / supporting quantitative research, for example: Bayesian statistics, programming in R, surveys, discrete choice experiments, and version control / Git