University College London
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PhD Studentships in Stereotypes, Classroom Social Networks, and Pupil Outcomes at UCL University College London in United Kingdom
Degree Level
PhD
Field of study
Education
Funding
Fully funded PhD studentship for 4 years. Home and international applicants are eligible.
Country
United Kingdom
University
University College London

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About this position
2 PhD studentships are available at University College London (UCL), linked to an ERC Starting Grant in the Boda Lab at the UCL Institute of Education, London.
The project examines how stereotypes spread through classroom social networks: who sees whom as “warm” or “competent,” why these perceptions persist, and how they may shape pupil outcomes and well-being. The research uses stochastic actor-oriented models and longitudinal social network analysis on new panel data from English secondary schools.
Applicants should have a first-class Master’s in sociology, psychology, or education. R skills are desirable. The project encourages candidates to bring their own research angle, especially if it connects to social networks, stereotypes, educational inequality, or adolescent development.
The studentships are fully funded for 4 years, and both home and international applicants are eligible. The post says applications are reviewed on a rolling basis, so early application is advisable.
Location: London, United Kingdom. Degree level: PhD.
Funding details
Fully funded PhD studentship for 4 years. Home and international applicants are eligible.
What's required
Applicants should have a first-class Master's degree in sociology, psychology, or education. R skills are desirable. The project invites applicants who can bring their own research angle and interest in stereotypes, classroom social networks, pupil outcomes, and well-being.
How to apply
Apply through the UCL studentship process and submit as soon as possible because applications are reviewed on a rolling basis. Prepare a strong proposal or research angle aligned with the project and highlight relevant quantitative or R skills.
More information can be found here
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