Research Fellow (Social Statistics - REALITIES)

Contract type: Full-time (35 hours per week)

Fixed-term: 21 months

We are looking for a postdoctoral Research Fellow with experience of using or creating geo-demographic profiles and of investigating the social determinants of health using theoretically-informed quantitative methods to join the new project, REALITIES in health disparities: researching evidence-based alternatives in living, imaginative, traumatised, integrated, embodied systems.

The opportunity:

As part of the new project, REALITIES in health disparities: researching evidence-based alternatives in living, imaginative, traumatised, integrated, embodied systems, you will co-create, validate, and disseminate a statistical Index of Community Assets (IoCA) to capture aspects of community and belonging in neighbourhoods that are not well represented in official statistics. The REALITIES project will explore how changes to health and social care systems can benefit deprived communities and people with experience of trauma, homelessness, poverty, unemployment, displacement, poor mental health or imprisonment.

This post is fixed term for 21 months available from asap.

This post is advertised as full-time (35 hours per week), however, we are open to considering flexible working patterns or requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.

Your skills and attributes for success:

• A PhD (completed or close to completion) in Social Statistics or Human/Health Geography. 
• Experience of investigating the social determinants of health using theoretically-informed quantitative methods, and of using or creating geo-demographic profiles
• Excellent statistical knowledge including working with spatial statistics and the use of statistical packages such as Stata and/or R
• Experience of working with a diverse set of social data including surveys, census, and administrative data
• Existing skills in, or capacity to develop skills in, web scraping to access text data on places from online sources