Principal Supervisor: Dr Tim Morris (UCL)

Co-Supervisors: Dr Emma Meaburn (Birkbeck); Professor Bonamy Oliver (UCL)

Project Description

Language and reading skills are key drivers of educational success, yet substantial inequalities emerge early in life as to why some children thrive in learning while others struggle. How do family experiences, schools, and children’s genetic differences work together to shape language and literacy development? How can this knowledge be used to improve early identification and educational support?

This PhD studentship offers a unique opportunity to answer these questions at the cutting edge of social science genomics, developmental psychology, and quantitative social science. The student will join a rapidly growing field that combines genetic data with rich large-scale longitudinal social data from cohort studies to understand how nature and nurture jointly shape children’s educational outcomes.

The studentship will be highly quantitative. You will work with large-scale UK birth cohort studies such as the Millennium Cohort Study that follow thousands of children from early childhood into adolescence, providing an unparalleled opportunity to examine how literacy and language skills develop over time. By applying innovative statistical and genetic methods, you will uncover how inherited propensities, family processes, and social contexts interact to influence educational outcomes.

We are looking for a highly motivated candidate with a strong foundation in, or a clear aptitude for statistical modelling/advanced quantitative analysis, computational skills, genetics, and an interest in the translation of research findings into meaningful insights for education and policy.

Training and development

This studentship provides exceptional interdisciplinary training, equipping the student with a highly sought-after skill set that spans genetics, statistics, and social science. The student will be embedded within UCL’s Centre for Longitudinal Studies (CLS), a world-leading research centre home to internationally renowned birth cohort studies that provides an unparalleled training environment. CLS provides an outstanding training environment, including workshops, doctoral networks, and collaboration opportunities across disciplines.

You will gain hands-on experience in advanced statistics, causal inference, genetic data analysis, and large-scale data management, alongside broader professional development in open science, research communication and policy engagement. You will be encouraged to publish in leading journals, present at international conferences, and collaborate across disciplines. You will also benefit from close supervision by an interdisciplinary team with expertise in genomics, social science, child developmental, statistics and bioethics. The project has direct policy relevance and will provide opportunities to engage with policymakers and education stakeholders, drawing on the networks of the supervisory team.

Aims and objectives

The overall aim of the project is to investigate how genetic, familial, and social environments jointly shape reading and language skills from childhood through to adolescence.

Specific objectives are to:

1. Improve prediction. Assess whether combining polygenic scores – which summarise genetic predisposition towards traits – with rich longitudinal social and family data improves early identification of children at risk for language and literacy difficulties.
2. Strengthen causal inference. Use family-based and quasi-experimental designs (including sibling comparisons) to distinguish direct genetic influences from shared family environment and background confounding.
3. Identify mechanisms. Usemother-father-child trio data to investigate how parents’ genetically influenced characteristics shape the home learning environment and, in turn, children’s development.
4. Inform policy and practice. Translate findings into actionable insights for educators, practitioners, and policymakers concerned with reducing inequalities in literacy outcomes.
5. Develop transferable research expertise. Provide the student with advanced interdisciplinary training in quantitative modelling, genomics, and longitudinal data analysis to support an independent research career.

Methodology

You will analyse large, nationally representative longitudinal cohort studies that include repeated measures of children’s language, reading, cognitive development, family environments and genomic data. These datasets provide exceptional statistical power and rich contextual information, enabling sophisticated modelling of developmental processes.

The project will combine several cutting-edge methodological approaches, including:

• Application of polygenic scores to capture genetic propensities linked to educational and language-related traits.
• Longitudinal multilevel modelling to examine developmental trajectories across childhood and adolescence.
• Sibling-comparison and within-family designs to strengthen causal inference by controlling for shared family background.
• Mother-father-offspring trio analyses to separate direct genetic effects from those that are mediated via environmental pathways which are shaped by parental genotypes (genetic nurture).
• Integration of social, environmental, and genomic data within reproducible computational workflows.

Subject Areas/Keywords

Education, genomics, development, cohorts, statistics, quantitative, modelling.

Key References

• Hart SA, Little C, van Bergen E. Nurture might be nature: cautionary tales and proposed solutions. NPJ Sci Learn. 2021 Jan 8;6(1):2. doi: 10.1038/s41539-020-00079-z. PMID: 33420086; PMCID: PMC7794571.
• Meaburn, E L (2025) Navigating genomics and education: insights, opportunities and challenges. Nuffield Foundation and Nuffield Council On Bioethics.
• Morris TT, Davies NM, Hemani G, Smith GD. Population phenomena inflate genetic associations of complex social traits. Science advances. 2020 Apr 15;6(16):eaay0328.
• Donati, G., Dumontheil, I., Pain, O., Asbury, K., & Meaburn, E. L. (2021). Evidence for specificity of polygenic contributions to attainment in English, maths and science during adolescence. Scientific Reports, 11(1), 3851.
• Bailey N, Wells T, Connolly E, Croker S, Jackson M, Latifi S, Marshall R, Roberts N, Sellen P, Sidhu K, Solel T, Taylor C, Whitfield S, Morris T. Genomics Beyond Health. What could genomics mean for wider government? Government Office for Science. Available at: https://assets.publishing.service.gov.uk/media/61efd002e90e07037ba76c7b/Genomics_Beyond_Health_Final_Report_Government_Office_for_Science.pdf
• Abdellaoui A, Yengo L, Verweij KJ, Visscher PM. 15 years of GWAS discovery: realizing the promise. The American Journal of Human Genetics. 2023 Feb 2;110(2):179-94.

Further details about the project may be obtained from:

Principal Supervisor: Tim Morris, t.t.morris@ucl.ac.uk

Co-Supervisor: Emma Meaburn, e.meaburn@bbk.ac.uk

Further information about PhDs at UCL is available from:

https://www.ucl.ac.uk/ioe/courses/graduate-research

How to Apply

Application forms and details about how to apply are available from:

Clare Elliott, UBEL DTP, clare.elliott@ucl.ac.uk

Closing date for applications is:

29^th March 2026