Research Fellow METIUS project (Internal only)

About us

Founded in 1902, UCL Institute of Education has been shaping policy and helping government, organisations and individuals navigate a changing society for the last 120 years. We embrace collaboration and excellence to create a future that is inclusive and just and have been ranked number one for education every year since 2014 in the QS World University Rankings by Subject.

The Social Research Institute, formerly the Department of Social Science, in the UCL Institute of Education, is one of the leading centres for social research in the UK. It is home to seven internationally renowned research units:

1. Centre for Longitudinal Studies
2. Centre for Time Use Research
3. CLOSER
4. EPPI Centre
5. Quantitative Social Science
6. Social Science Research Unit
7. Thomas Coram Research Unit

More than 180 academic, research, teaching, technical and professional service staff work in the department. In addition to the seven research centres, it is home to three undergraduate degrees, three master’s programmes and a thriving doctoral community.

About the role

We are seeking to appoint a Research Fellow to contribute to the AI work package within Mobilising Evidence Through AI and User-informed Synthesis (METIUS) project supporting the responsible development and use of AI-enabled approaches for living evidence synthesis. The role will involve working with interdisciplinary teams to help design, evaluate, and implement AI-supported methods and tools that enhance the timeliness, transparency, and rigour of evidence synthesis. This may include contributing to methodological research, engaging with evidence users and stakeholders to understand their needs, supporting evaluations of AI applications, and helping to establish best practices for the safe and effective integration of AI into evidence synthesis workflows.

This post is open to internal UCL applicants only.

This post is funded on a full-time basis with an anticipated start date of 01 August 2026 until 30 September 2030. For further queries please contact .

About you

You will have a PhD in relevant discipline, or equivalent experience in a relevant field. In-depth knowledge and experience of using EPPI Reviewer and its associated machine learning tools. Successful record of effective completion of systematic review and other research projects. Proficiency in one or more relevant programming languages (e.g., Python, R, JavaScript).

Your application form should address all person specification points and clearly demonstrate how your skills and experience meet each of the criteria. It is important that the criteria are clearly numbered and that you provide a response to each one.

Customer advert reference: B16-02181

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