Vacancy ID:
11323
Location:
Leicester
Department:
Population Health Sciences
Vacancy terms:
Full-time, part-time (minimum 0.5FTE, 18.75 hours per week), or job share considered, fixed term contract until 28 February 2026
Salary details:
Grade 7 - £39,105 to £45,163 per annum, pro-rata if part-time
Hours per week:
37.5
12 Feb 2025
About the role

The Biostatistics Research Group are looking to appoint a Research Associate interested in statistical methodology to undertake a project on calibration drift in prognostic models.

The research team has previously developed temporal recalibration1,2, a method which takes account of improvements in survival over time to ensure that the predictions that prognostic models produce are as up-to-date as possible and relevant to current patients.

The aim of this project is to maximise patient benefit from prognostic models by extending and making temporal recalibration methods easily accessible for researchers.

Supported by the project leads and research team, the Research Associate will:

  1. Use simulation studies to determine how best to internally validate models developed using temporal recalibration, with and without competing risks
  2. Develop software packages (in Stata and/or R) and web-based tutorials to aid with the uptake of temporal recalibration methodology

They will also have the opportunity to present research findings at international conferences and attend specialist training courses.

References:

1 Booth S, Riley RD, Ensor J, Lambert PC, Rutherford MJ. Temporal recalibration for improving prognostic model development and risk predictions in settings where survival is improving over time. Int J Epidemiol. 2020;49(4):1316-1325.

2 Booth S, Mozumder SI, Archer L, Ensor J, Riley RD, Lambert PC, Rutherford MJ. Using temporal recalibration to improve the calibration of risk prediction models in competing risk settings when there are trends in survival over time. Stat Med. 2023;42(27):5007-5024
About you

You will have a PhD (or equivalent) in a relevant discipline. Knowledge of methodology for prognostic models, survival analysis and competing risks would be highly beneficial for this role as well as experience of analysing electronic health records.

Additional information

Informal enquiries are welcome and should be made to Sarah Booth on [email protected]

Applications for job share will be considered.

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. More information regarding secondments can be found here
 
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
 
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.
 
As a diverse and forward-thinking employer, we embed the principles of equity, diversity and inclusion into everything we do. That includes not just our core missions of teaching and research, but also our support for staff, students and our local community through our values of Inspiring, Impactful and Inclusive through our values of Inspiring, Impactful and Inclusive.
 
We’re committed to the wellbeing of all our staff and to the sustainability of our environment, on our campus and beyond. We offer a competitive salary package, excellent pension scheme and a generous annual leave allowance, along with opportunities to develop your career in a supportive and collaborative environment.

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