Project title: Beyond Nature vs Nurture: A Sociogenomic Analysis of Life Outcomes
Primary supervisor: Dr Weilong Zhang (University of Cambridge)
Second supervisor: Professor Marco Francesconi (University of Essex)
Third supervisor: Professor Eric French (University of Cambridge)
University: University of Cambridge
SENSS Partner Institution: University of Essex
SENSS Theme: Advanced Methods for Social & Economic Research
Degree structure: The structure of the studentship offered will depend on your personal training needs. However, the minimum duration of a SENSS-funded studentship will be 3.5 years: this covers a PhD and a mandatory placement of approximately 3 months. The maximum duration of a studentship will be 4.5 years: this covers a Masters degree followed by a PhD, as well as the mandatory 3-month placement.
Project aims and objectives
Aim: To understand how genes and environments jointly shape life outcomes, and to identify policy levers that can amplify opportunity.
Objectives:
Build and validate PGS (for traits such as education, risk, and cognition) and link them to socioeconomic outcomes.
Estimate design-based G×E effects through policy, place, and cohort interactions, and develop structural life-cycle models focusing on mechanisms such as schooling, occupation, fertility, and savings.
Translate findings into policy-facing outputs (policy briefs, seminars, blog posts) to reach both academic and policy audiences.
Disseminate research via peer-reviewed journal articles and presentations at international conferences.
Project background
This collaborative PhD studentship investigates how genetic predispositions and real-world environments combine to shape education, careers, earnings, and family formation. The project leverages genome-wide methods to construct polygenic scores (PGS) and test gene–environment (G×E) interactions across the life course. Using large-scale datasets such as the UK Biobank and Understanding Society, the study will integrate cutting-edge genetic data with advanced econometric and structural modelling approaches. The findings will provide timely insights into the interplay between genetics and socioeconomic outcomes, informing evidence-based policies in education, health, and social mobility.
Training opportunities
A comprehensive training package will be designed in consultation with the supervisory team and collaborative partner (European Social Science Genetics Network). Training will cover:
Methods: Advanced econometrics, causal inference, machine learning for genetics (e.g., LDpred2 PGS), and survey/administrative data linkage.
Coding: R, Stata, Python, and MATLAB, with workflows for handling secure, large-scale datasets.
Professional skills: Research communication, knowledge exchange, open science practices, and engagement with policy stakeholders.
Networks: Participation in Cambridge and Essex seminar series, SENSS training modules, and the ESSGN boot camp, alongside funded opportunities for conference presentations.
Essential and/or desirable attributes/skills
Essential:
Strong quantitative skills in econometrics, statistics, or data science.
Clear writing and communication skills.
Intellectual curiosity for interdisciplinary work and a willingness to learn new methods.
Desirable:
Experience with large-scale or administrative datasets.
Prior exposure to genetics or polygenic score methods.
Coding proficiency in R, Stata, Python, or MATLAB.
Completion of a methods-focused Master’s degree (or equivalent experience).
Studentship details
Studentships are advertised as being between +3.5 and +4.5-year. The standard length of an ESRC-funded studentship is +3.5. This includes the standard +3 PhD, plus an +0.25 (one term) for the integrated placement which you must take as part of your studentship, and a further additional +0.25 (one term) to enable you to undertake training relevant to your research project (including career progression). All studentships are offered on either a full-time or part-time basis.
The studentship award covers your university fees up to the home rate and provides you with a stipend (£20,780 in 25/26). You will also be able to apply for additional funding via the CAM-DTP discretionary fund to support your training needs.
Residential eligibility
All applicants, whether Home or International, are eligible for an award that covers tuition fees up to the home rate.
International students will not be expected to use their own resources to pay tuition fees at the international rate; precise arrangements for this will be advised to the successful candidates.
How to apply for this studentship
To be considered for this SENSS-CAM studentship, you will need to make an application to CAM-DTP for this SENSS-CAM studentship.
The deadline for submitting your application for SENSS-CAM funding on HEIApply is 09:00 GMT on 7 January 2026. No extensions to this deadline will be permitted.
Please read the SENSS-CAM Studentship Application Guidance Notes before completing the online application form via HEIApply. The Guidance Notes are available here.
Candidates must also have applied for a place to study at the host university by the same deadline. Candidates who apply for funding on HEIApply but have not applied for place to study at the host university will not be eligible for consideration of funding.
Please go to University of Cambridge for information on how to make your application. The deadline applying to University of Cambridge for a place is 23:59 GMT on 2 December 2025.
For details on how to apply to the University of Cambridge, please see: How & When to Apply https://www.econ.cam.ac.uk/apply/postgraduate/courses/phd-economics/how-when-apply.
Important: To be eligible for consideration for this funding, you must nominate Dr. Weilong Zhang as your proposed supervisor in your University of Cambridge application.
Enquiries
For enquiries about this research project, please email Dr. Weilong Zhang, University of Cambridge (wz301@cam.ac.uk) or Prof. Marco Francesconi, University of Essex (mfranc@essex.ac.uk)
For enquiries related to your eligibility for this studentship, and/or the application process, please email: econgrad.admit@econ.cam.ac.uk.
About SENSS
The South and East Network for Social Sciences (SENSS) is a consortium formed of eight leading UK universities, all of which are engaged in cutting-edge social science research and training. The SENSS consortium members are:
City St George’s, University of London
Cranfield University
Goldsmiths, University of London
Middlesex University
University of East Anglia
University of Essex (the co-ordinating institution)
University of Lincoln
University of Roehampton
SENSS offers a world-class inter-disciplinary PhD research and training environment. It is committed to supporting its internationally recognised researchers and to producing the next generation of talented social scientists. SENSS has been accredited as a prestigious Doctoral Training Partnership (DTP) by the Economic and Social Research Council (ESRC), the national body which funds research and training in economic and social issues.
We pride ourselves on our rigorous doctoral training programme, making the most of our members’ diverse specialisms and offering our students a wide array of subject specific as well as advanced training opportunities. SENSS offers high-calibre supervision, driven by our members’ emphasis on formal training and research culture.
For further information about SENSS, please visit the SENSS website
About CAM-DTP
The CAM Doctoral Training Partnership [DTP] is a consortium between Anglia Ruskin University (ARU), the University of Bedfordshire (UoB) and the University of Cambridge (UoC).
Its collective environment of excellent research and impact is an ideal complement for the interdisciplinary training of diverse social scientists. CAM-DTP PhD students will join a hub for regional change addressing key societal challenges and the DTP is keen to attract talented doctoral researchers from a wide range of backgrounds. www.cam-dtp.ac.uk