Research Assistant in Microsimulation Modelling

The University of Leeds is seeking to appoint a talented and highly motivated Research Assistant to join The SIPHER Consortium, a large UK public health research initiative, established with funding from the UK Prevention Research Partnership (UKPRP). 

SIPHER is developing research to prevent physical and mental ill health, and tackle persistent health inequalities. SIPHER is a multidisciplinary, multi-institution partnership bringing together six universities, policy partners at local, regional and national scales of Government, including: Scottish Government, Greater Manchester Combined Authority and Sheffield City Council, as well as a large number of senior practice partners.

You will work with the SIPHER team to develop dynamic microsimulation models that capture the dynamic relationships between income, housing and health. You will use these models to produce estimates of distributional (inequality) impacts needed for policy appraisal at high spatial resolution and assesses the evolution over time of effects in the system. You will liaise with other SIPHER researchers to formulate dynamic model structures, use data from a range of sources, and knowledge elicited from experts to build models for prediction and provide quantification of associated uncertainties. You will calibrate and validate these models in close dialogue with other SIPHER researchers and practice partners.

To explore the post further or for any queries you may have, please contact:

Nik Lomax, Professor of Population Geography
Email: [email protected]

Location:  Leeds – Main Campus
Faculty/Service:  Faculty of Environment
School/Institute:  School of Geography
Category:  Research
Grade: 
Grade 6
Salary: 

£30,487 to £36,024
per annum
Working Time:  100% – We are open to discussing flexible working arrangements.
Post Type: 

Full Time
Contract Type:  Fixed Term (until 15 September 2024)
Release Date:  Friday 08 September 2023
Closing Date:  Friday 15 September 2023
Reference:  ENVGE1217
Downloads:  Candidate Brief