Location: | Leicester, Hybrid |
---|---|
Salary: | £39,105 per annum, pro-rata if part-time, due to funding restrictions. Grade 7 |
Hours: | Full Time, Part Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 22nd October 2024 |
---|---|
Closes: | 24th November 2024 |
Job Ref: | 10864 |
Full-time, or job share considered, fixed term contract until 31 December 2025
Hours per week: 37.5
About the role
We are looking for a talented, motivated individual to join the Biostatistics Research Group to undertake methodological research funded by the NIHR Research for Patient Benefit Programme.
The Biostatistics Research Group within the Department of Population Health Sciences specialises in the development, application and teaching of statistical methods in medical research with the ultimate aim of improving the health of the population. A particular strength of the group is the transferral of novel statistical methodology into practice through the development of software, use of novel methods in applied studies through collaboration with both internal and external clinicians, development of guidelines for policy-makers and teaching on specialist courses.
We are looking for an excellent researcher with an interest in clinical trial methodology to lead a project looking at Identifying methodological uncertainties in the design and analysis of trials in people living with multiple long-term conditions. The project includes undertaking a systematic review of current trials in this disease area to understand current practice followed by a consensus study using a Delphi approach to prioritise methodological uncertainties for future methodological research. At the end of the study we will hold a workshop to disseminate the findings and develop working groups to address the priority issues.
The post-holder will work collaboratively and independently as part of the research team. The post-holder will work closely with the project lead, co-investigators and steering group to complete the required research. This role requires expertise and interest in the design and analysis of clinical trials. The post-holder will be responsible for completing the systematic review, developing the protocol for the consensus study and managing ethical approvals, and conducting the Delphi study. They will also contribute to the dissemination of research findings through publications, presentations, and stakeholder engagement activities. Hybrid working is allowed, the post-holder would be expected to be present in the department a minimum of 2 days a week.
About you
Educated to PhD level in a relevant discipline (such as medical statistics) you will have experience in clinical trials and evidence of contributions to peer-reviewed publications. Experience of conducting systemic trials or consensus studies, public and patient involvement, clinical trials methodology research or in obtaining ethical approval, would be beneficial but is not essential.
The University of Leicester prides itself on the diversity of its student population and on being an inclusive employer. We encourage applications from candidates who represent the diversity of our student population, local communities and wider society. In particular, we welcome applications from Black, Asian and minority ethnic candidates, as this is a staff group currently underrepresented in the University
Additional information
Informal enquiries are welcome and should be made to Professor Laura Gray on lg48@leicester.ac.uk.
As part of the University’s ongoing commitment to professional development, this role will also be considered on a seconded basis for existing staff members. Please ensure this is discussed with your line manager prior to applying.
The University of Leicester has been changing the world, and changing people’s lives, for 100 years. When you join us, you’ll become part of a community of Citizens of Change, which includes not only our staff and our current students but also thousands of Leicester graduates around the world.
Advert closes midnight on: 24 November 2024
Type / Role:
Subject Area(s):
Location(s):