PhD studentship opportunity: Causal Inference in Developmental Psychology

2025-09-16 2 min read

This PhD will explore how recent advancements in statistics and data science can be integrated to modernise developmental research. Specific topics include:

  1. Theory of causal identification and inference based on potential outcomes and graphical models highlights the importance of study design (how data are collected and preprocessed).
  2. Research in epidemiology and biostatistics (e.g. Robins’ g-methods and dynamic treatment regimes) and economics (e.g. instrumental variables, difference-in-differences) provides new methods for observational studies.
  3. Machine learning provides new tools to train flexible statistical models with complex data (possibly unstructured, such as images and texts).

These advancements are underutilized in developmental psychology but hold great potential. Applying advanced statistical methods can transform our understanding about the mechanisms and complex interplay of different factors in psychological and cognitive development.

ESRC Research Priority Areas

  • Health and Social Care
  • Understanding Behaviour

Research skills you must have if applying for this topic

Solid understanding in undergraduate mathematical statistics (inc. maximum likelihood estimator, generalized linear models); Prior experience with data analysis in a practical context

Research skills it would be helpful to have if applying for this topic

Basic understanding in developmental psychology; Proficiency in R/Python programming; Advanced mathematical statistics (e.g. asymptotic theory and nonparametrics); Interdisciplinary study experience

Supervisory Team

Professor Qingyan Zhao (Department of Pure Mathematics and Mathematical Statistics, University of Cambridge) qz280@cam.ac.uk

Professor Gordon Harold (Faculty of Education, University of Cambridge) gth25@cam.ac.uk

Professor Pasco Fearon (Department of Psychology, University of Cambridge) pf380@cam.ac.uk

More information

This is an interdisciplinary PhD project and funding is subject to an internal competition by CAM-DTP. More information can be found on the CAM-DTP website.