Research Assistant — Education Data & Inequality (Hybrid)

UCL; Greater London; On-site; GBP 36,000 - 43,000; Part time

Benefits offered by this job

41 Days holiday

Relocation scheme

On-site nursery

On-site gym

CARE pension

Cycle to work

Season ticket loan

Immigration loan

Staff Support Service

Medical insurance discount

Job summary

UCL invites applications for Research Assistant- 0.4FTE in London to support the STERN project. The role focuses on developing questionnaires, selecting samples, and recruiting schools for data collection across England. This is a part-time, on-site position within the School of Education.

The candidate should hold a master’s degree in a relevant social science and have experience with quantitative methods; proficiency in R is essential. Closing date is 2 November 2026.

Qualifications

• Master’s degree in a relevant social science discipline (sociology, social psychology, education, behavioural science, or related field) or equivalent research experience.
• Experience in quantitative research methods and an interest in social inequalities, social networks, or stereotypes.
• Experience with statistical software and willingness to develop proficiency in R.

Responsibilities

• Support development of the questionnaire for the STERN project.
• Assist with sample selection and recruitment of participating schools.
• Support data collection and data management activities.
• Contribute to potential own research projects using project data.

Skills

Quantitative methods

R programming

Social inequalities

Education

Master's degree

Tools

R

Job description

UCL invites applications for Research Assistant- 0.4FTE in London to support the STERN project. The role focuses on developing questionnaires, selecting samples, and recruiting schools for data collection across England. This is a part-time, on-site position within the School of Education.

The candidate should hold a master’s degree in a relevant social science and have experience with quantitative methods; proficiency in R is essential. Closing date is 2 November 2026.