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Research Assistant in Medical Statistics

Job in Sheffield, South Yorkshire, S5, England, UK
Listing for: The University of Sheffield
Full Time position
Listed on 2025-12-30
Job specializations:
  • Research/Development
    Research Scientist, Clinical Research
  • Healthcare
    Clinical Research
Job Description & How to Apply Below

Research Assistant in Medical Statistics

Join to apply for the Research Assistant in Medical Statistics role at The University of Sheffield

This post offers a competitive salary and a range of benefits including flexible working, a generous pension scheme, and opportunities for professional development.

Overview

The Design, Trials, and Statistics section in the Division of Population Health based in the School of Medicine and Population Health is seeking a research assistant in medical statistics with a passion for statistics and applied research. The post is based within the Clinical Trials Research Unit (CTRU). Suitable candidates will have at least two years of work experience in clinical trials, particularly adaptive designs, ideally in an academic setting.

Applicants will possess good knowledge of applied statistics and statistical theory, including response adaptive randomisation and crossover trials. They will have strong programming skills and experience working with complex datasets, a “can do” attitude, flexibility, and excellent communication skills to explain complex concepts in lay terms.

Main Duties And Responsibilities
  • Undertake the statistical analysis of research projects (primarily randomised controlled trials) in line with pre‑defined statistical analysis plans and contribute to their reporting and dissemination, under the supervision of a senior statistician.
  • Draft statistical analysis plans for new trials, in line with the analysis outlined in the protocol and grant application, under the supervision of a senior statistician.
  • Contribute to applied methodological research for the design, conduct, analysis and reporting of studies that evaluate new health technologies, specifically the ‘Enhancing the design, conduct and analysis of Adaptive and Platform Trials through consensus‑driven Statistical Analysis Plan guidance (APT‑SAP)’ project.
  • Provide high‑quality statistical advice and support to multidisciplinary research projects within the Division of Population Health, under the supervision of a senior statistician.
  • Contribute to outputs that will inform academic publications in high‑quality journals.
  • Attend and participate in relevant department meetings.
  • Continually update knowledge and understanding of medical statistics in line with advances in the relevant subject area.
  • Share knowledge and skills with colleagues.
Teaching
  • Contribute to teaching statistics in tutorials to undergraduate and postgraduate students in the school with training provided as appropriate.
Planning and Organising
  • Assist with the high‑quality delivery of research studies within agreed timescales.
  • Prioritise tasks and allocate time to different studies as appropriate.
  • Undertake advance planning to meet deadlines for study milestones and dissemination of results.
  • Develop materials for research study meetings as requested.
  • Carry out other duties commensurate with the grade and remit of the post.
Person Specification

Our diverse community recognises unique abilities, backgrounds, and beliefs. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn’t match perfectly, your contribution is valuable, and we encourage you to apply. Please reference the application criteria in your statement when you apply.

Essential Criteria
  • MSc containing substantial statistical content, as well as medical applications.
  • Minimum of 3 years work experience, and awareness of the principles of good clinical practice and of regulatory and ethics requirements of clinical trials.
  • Experience of undertaking, interpreting and presenting complex statistical analyses, including for crossover trials, and studies in rare diseases.
  • Statistical programming experience in either Stata or R, including complex statistical models (i.e. crossover designs and involving both Bayesian and frequentist methods), and creating automated statistical reports and other relevant output from within statistical software.
  • Track record of publications in clinical and methodological journals.
  • Experience in collaborating on the methodological development of value‑based randomisation, including publishing in this area.
  • Experience in…
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