We seek an experienced Medical Statistician to analyse high-dimensional data arising from the integration of molecular, genomic and imaging data with clinical information from electronic health records to identify causal risk factors associated with a range of diseases. The post-holder will have access to rich, unique datasets from multiple population and patient cohorts, which include genetic, multi-omic and EHR data. This post will be co-supervised between HDR UK-Cambridge and the MRC Biostatistics Unit, providing access to statistical and health informatics expertise.

Candidates should have: i) a Masters or PhD in Statistics or another relevant subject; ii) strong statistical/quantitative skills and knowledge of high-dimensional statistical methods (eg. LASSO, ridge regression); iii) excellent statistical programming skills (e.g. Stata, R); iv) high-level report writing and presentation skills and; v) excellent verbal and written communication skills.

Health Data Research UK is the new national institute for data science for health, established in 2018 with long term (10 year+) funding support from research councils, UKRI, charitable and governmental research funders. The mission of HDR UK is to drive improvements in the health of patients and populations through research at regional and national scale. To deliver this mission, the Wellcome Sanger Institute (WSI), EMBL-European Bioinformatics Institute (EBI), and the University of Cambridge (UoC) and its associated hospitals came together as the HDR UK-Cambridge partnership.

Health Data Research UK is funded by UK Research and Innovation, Department of Health (England) and the UK devolved administrations, and leading medical research charities.

The Medical Research Council (MRC) Biostatistics Unit (BSU) is one of the largest groups of biostatisticians in Europe, and a major centre for research, training and knowledge transfer in biostatistics.

Essential Skills

  • Masters or PhD in Statistics or another relevant subject
  • Strong statistical/quantitative skills and knowledge of high-dimensional statistical methods (eg. LASSO, ridge regression)
  • Excellent statistical programming skills (e.g. Stata, R)
  • High-level report writing and presentation skills
  • Strong organisational and interpersonal skills
  • Excellent verbal and written communication skills
  • Ability to judge priorities and work to tight deadlines
  • Ability to be productive and energetic
  • Ability to work to targets both independently and within a team environment
  • Ability to ensure accuracy and rigour in all areas of work
  • Ability to correctly interpret scientific data

Ideal Skills

  • Experience of relevant statistical approaches, eg, joint models for the analysis of longitudinal and time-to-event model or Mendelian randomisation
  • Analysis of large, complex epidemiological datasets
  • A track record of authoring scientific publications
  • Experience of version control (e.g. GIT)

Other information

Please include a CV and a cover letter describing your skills with your application.

Closing Date: 01 December 2019

Job Reference: 83716 

If you would like further information or to have an informal discussion about the role, please contact the hiring manager through: mc27@sanger.ac.uk

Job description

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