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Senior Research Associate in Medical Statistics

University of Bristol - Translational Epidemiology

Location: Bristol
Salary: £42,632 to £47,874 per annum, Grade: J/Pathway 2
Hours: Full Time, Part Time
Contract Type: Permanent
Placed On: 20th December 2024
Closes: 13th January 2025
Job Ref: ACAD107884

The role

We have an exciting opportunity for a talented medical statistician with expertise in evidence synthesis to join the BEAM (Bristol Evidence synthesis, Appraisal and Modelling) Centre at University of Bristol.

BEAM brings together researchers working on evidence synthesis and modelling across Bristol Medical School. BEAM is an internationally renowned centre of excellence in evidence synthesis and is the only centre to host all three types of NIHR funded Evidence Synthesis Groups (ESGs), providing access to a wealth of knowledge and expertise in evidence synthesis across a broad range of topics and clinical areas.  

You will work primarily with the three NIHR ESGs: Bristol ESG, Bristol Evidence Synthesis for Screening (BESS) and Bristol-UCL-Kings Living Systematic Review (BUcKLES) groups, but with some flexibility to contribute to work of other research groups within BEAM where needed. Bristol ESG is one of nine ESGs producing evidence reviews on a wide range of topics for the NIHR. The newly funded BESS group will conduct evidence syntheses to support the work of the UK National Screening Committee (NSC). The BUcKLES group, also newly funded, is the only ESG dedicated to undertaking living systematic reviews. 

You will be part of a multidisciplinary team including systematic reviewers, statisticians, information specialists, qualitative researchers, health economists, clinicians and public contributors. 

The post is available from 1 April 2025 with funding for up to 5 years.

Requests for flexible working patterns will be considered.

What will you be doing?

You will work on a range of applied quantitative evidence syntheses, contributing to projects across BEAM’s three NIHR ESGs. There may also be opportunities to contribute to methodological work related to evidence synthesis.

You will be required to:

  • Perform meta-analysis, network meta-analysis and other statistical evidence syntheses across a wide range of topics
  • Extract, check and/or manipulate statistical data from primary research studies
  • Communicate effectively with researchers of included studies for data clarifications or to request additional data as required
  • Maintain clearly documented statistical code for all projects
  • Contribute to reports for the NIHR and National Screening Committee
  • Contribute to peer reviewed publications, grant proposals and conference presentations
  • Build and maintain collaborative relationships with all research partners

You should apply if

  • You have expertise in meta-analysis, ideally including network meta-analysis
  • You are proficient with statistical packages including R or Stata, and have experience with or are enthusiastic to learn to undertake Bayesian analyses, using e.g. WinBUGS/JAGS
  • You have an understanding of primary study designs (e.g. randomised controlled trials and diagnostic test accuracy studies) and of systematic reviews and their role in evidence-based health care and decision making
  • You have a PhD in a relevant discipline, or equivalent research experience, and a track record of publication of research papers in peer reviewed journals
  • You have enthusiasm for evidence synthesis and contributing to evidence-based decision making

Additional information

Contract type: Open-ended with funding until 31/03/2030

Work pattern: Full-time/ 1 FTE (part-time considered)

Shift pattern: 35 hours per week (part-time considered)

For informal queries please contact: Dr Hayley Jones, hayley.jones@bristol.ac.uk

Our strategy and mission

We recently launched our strategy to 2030 tying together our mission, vision and values.

The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential.

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