Research Fellow - Cochrane Reviews / Evidence Synthesis

Research Fellow - Cochrane Reviews / Evidence Synthesis

Full-Time 51270 - 51270 £ / year (est.) No working from home possible
Collabdemy

At a Glance

  • Tasks: Join a team to conduct systematic reviews and evidence synthesis in child health.
  • Company: Collaborative programme with Cochrane Cystic Fibrosis and global network.
  • Benefits: Competitive salary, research experience, and opportunities for publication.
  • Other info: Dynamic research environment with opportunities for career growth.
  • Why this job: Make a real impact in child health research and work with leading experts.
  • Qualifications: PhD in relevant discipline and experience in systematic reviews.

The predicted salary is between 51270 - 51270 £ per year.

This post offers an exciting opportunity to join a collaborative programme of systematic review work conducted jointly with Cochrane Cystic Fibrosis and the wider Cochrane global network. The post-holder will contribute to the delivery of a suite of Cochrane reviews and related evidence synthesis outputs in child health, including reviews addressing key questions in cystic fibrosis and perinatal infection. The work will draw on Cochrane’s established methodological framework and will involve working closely with the Cochrane Information Specialist, Managing Editor, academic supervisors and wider project collaborators.

The role will include developing review protocols, screening studies, extracting data, undertaking risk-of-bias assessment, synthesising evidence, performing meta-analysis where appropriate, and preparing manuscripts for publication in the Cochrane Library and/or peer-reviewed journals.

About the person:

  • Have or about to obtain PhD in relevant discipline.
  • Significant research experience and skills relevant to evidence synthesis, paediatrics, infection, epidemiology, or another field aligned to the programme of work.
  • Experience conducting systematic reviews, preferably including familiarity with Cochrane methodology (e.g., protocol development, study selection, data extraction, risk‐of‐bias assessment, and synthesis).
  • Demonstrated experience of research methods and techniques pertinent to evidence synthesis, such as meta‐analysis, narrative synthesis, diagnostic test accuracy reviews, or other methodologies relevant to the post.
  • Experience using systematic review software and analytical tools, or statistical software appropriate for meta‐analysis.
  • Experience working with clinical, epidemiological, or diagnostic data, and an ability to understand and interpret study designs commonly used in clinical research.
  • Experience of project management, delivering research outputs to deadlines, and proven ability to work effectively within a multi‐disciplinary research environment.
  • A good presentation and publication record commensurate with career stage, including contributions to peer‐reviewed outputs.

To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information on our website.

£42,972 to £51,270 per annum

Research Fellow - Cochrane Reviews / Evidence Synthesis employer: Collabdemy

Queen Mary University of London is an exceptional employer, offering a vibrant work culture that prioritises diversity and inclusion. As a Clinical Research Fellow in Gastrointestinal Medical Oncology, you will be part of a leading institution renowned for its research excellence and commitment to improving health outcomes in diverse communities. With competitive salaries, generous leave, and extensive professional development opportunities, Queen Mary fosters an environment where employees can thrive both personally and professionally.

Collabdemy

Contact Details:

Collabdemy Recruitment Team

We think you need these skills to ace Research Fellow - Cochrane Reviews / Evidence Synthesis

PhD in relevant discipline
Research experience in evidence synthesis
Systematic reviews
Cochrane methodology
Protocol development
Study selection
Data extraction