Research Associate / Doctoral Candidate (m/f/d)

The Professorship for Learning Analytics (LEAPS) at the TUM School of Social Sciences and Technology, Technical University of Munich, is seeking a Research Associate / Doctoral Candidate (m/f/d) Participatory Practices for Fostering Data Agency.

The position is TV‑L E13, 50%, initially limited to 3 years. Applications are reviewed on a rolling basis (first come, first served). Application deadline: 25 March 2026.

About Us The candidate will be a part of the LEAPS research group (LEarning Analytics and Practices in Systems) led by Prof. Dr. Oleksandra Poquet. LEAPS investigates how data from learning environments can support agency and social networks in higher education and workplace training. The group is part of the TUM School of Social Sciences and Technology, the Munich Data Science Institute, and the TUM EdTech Centre.

Project Description

Educational technologies collect more learner data than ever, but learners have little say in what happens with it. The project aims to change that by developing ways to measure and strengthen data agency so that learners can make real, informed choices about their data in learning environments. The doctoral researcher will develop measures for data agency and investigate them in relation to participatory consent practices in digital learning. The focus is on designing, conducting, and evaluating interventions that go beyond conventional consent mechanisms and actively involve learners in engaging with their data. The position includes some teaching in the areas of educational technology and learning analytics.

Your Profile

• Completed Master’s degree (or equivalent) in psychology, sociology, education, behavioural sciences, or a related field; candidates from HCI with strong quantitative research experience are also welcome
• Strong skills in experimental research methods and statistical data analysis
• Experience in designing and conducting experiments, ideally with online experiment tools (e.g., Gorilla, Qualtrics, oTree, or similar)
• Knowledge of psychometrics and/or scale development is an advantage
• Proficiency in statistical software (e.g., R, SPSS, or similar)
• Interest in data ethics and privacy in education
• Ability to work independently
• Demonstrated academic writing ability (e.g., Master’s thesis, publications, or conference contributions)
• Excellent written and spoken English; German language skills are an advantage
• Ability to work in an interdisciplinary team

What We Offer

• Remuneration according to TV‑L E13 (50%)
• Excellent mentorship and academic supervision
• Strong international and local network
• Doctoral training through the TUM Graduate School
• Active involvement in academic communities
• Flexible working arrangements
• Access to the excellent research infrastructure of TUM and the Munich Data Science Institute

Please send your complete application (motivation letter, CV, transcripts, Master’s thesis or relevant publications, contact details of references) as a PDF to:

TUM is an equal opportunity employer committed to increasing the proportion of women in its workforce. Applications from women are therefore expressly encouraged. Candidates with disabilities who are otherwise equally qualified will be given preference. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information

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