The Institute for Global Prosperity is an interdisciplinary research institute at UCL. It develops new frameworks for measuring and advancing prosperity beyond GDP. IGP leads three prosperity measurement programmes: the Citizen Prosperity Index (CPI), the Maisha Bora Index (Kenya), and the Good Life Euston Index (Camden). The CPI is derived from the East London Longitudinal Study (2021 to 2031), a decade-long research programme tracking prosperity across east London through repeated household surveys of approximately 4,000 residents, covering Tower Hamlets, Newham, Hackney, and Barking and Dagenham. IGP coordinates the BENEFITS Horizon Europe project, a seven- country, €3 million research programme on beyond-GDP indicators. The Data and AI for Social Purpose research theme drives methodological innovation in composite index construction, small-area estimation, and applied social data science.
Placement opportunity
The Citizen Prosperity Index (CPI) is IGP’s flagship multidimensional prosperity measure, derived from the East London Longitudinal Study and now scaled nationally using secondary microdata. As the index matures and gains policy traction, a set of questions becomes pressing.
How does the CPI compare with established frameworks such as the Index of Multiple Deprivation, the ONS Measures of National Wellbeing Dashboard, and the SAGE index?
Where do they converge, where do they diverge, and what does each capture that the others miss? Can beyond-GDP frameworks designed for national comparison be meaningfully disaggregated to subnational level? And can the CPI’s own methodology be improved through alternative weighting strategies, machine learning approaches to dimension validation, or structural equation modelling?
This placement offers a PhD student the opportunity to investigate one or more of these questions. The student will work with a range of secondary data sources and will be expected to identify and use the datasets best suited to their research focus. Expected outputs are one to two research papers, with the student credited as co-author. Outputs with particular policy relevance may also be developed for non-academic audiences as part of IGP’s engagement with national and international partners, including the SAGE index team.
The student will be supervised by Professor Saffron Woodcraft and embedded within the Data and AI for Social Purpose research team. Regular supervision meetings will be held throughout, with access to IGP’s data infrastructure and research network.
Skills and experience required for the role
Essential: strong quantitative methods, experience with survey or panel data, proficiency in R, Python, or Stata.
Desirable: familiarity with composite index construction or the wellbeing measurement literature, knowledge of beyond-GDP measurement frameworks, experience with small- area estimation or spatial analysis, and interest in applied social data science.
Working arrangements and location of the placement
The placement will be conducted fully remotely. The student is not required to attend UCL in person, though this can be arranged if preferred. Flexible working arrangements can be discussed at the point of offer. Reasonable travel and subsistence costs will be reimbursed.
How to apply
Applicants should submit a CV and a cover letter (no more than two pages) outlining their relevant skills and motivation.
Applicants will also need to submit an ESRC placement and funding permissions form with their application.
Applications should be sent to n.tzivanakis@ucl.ac.uk with the subject line “ESRC RiP Application: CPI Placement.”
Closing date: 30/04/2026
Anticipated start date: 01 June 2026, or as soon as possible thereafter. We are flexible on start date.
Recruitment process
Applications will be reviewed by the host. Shortlisted candidates will be invited to an informal online conversation to discuss the project and their experience. Applicants will be notified of the outcome within two weeks of the closing date.
Any queries about this opportunity should be addressed to the host organisation: Dr Nikolaos Tzivanakis, Senior Research Fellow and Head of Data, UCL Institute for Global Prosperity. n.tzivanakis@ucl.ac.uk