University of Tübingen is seeking a highly motivated PhD candidate with a background in Psychology, Empirical Educational Research, Educational Science, Data Science, Statistics, Economics, Learning Sciences, or a related field to join TRACE at the Hector Research Institute of Education Sciences and Psychology, University of Tübingen. The PhD candidate will join a vibrant international research environment with close supervision and extensive opportunities for methodological and professional development.
Table of Content
Summary
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Benefits
We provide an inspiring, productive, and collaborative research environment with excellent opportunities for professional and academic development. Specifically, we offer:
- Comprehensive supervision and a wide range of training opportunities, including methodological training as part of early-career researcher support.
- The opportunity to contribute to cutting-edge research at the intersection of learning analytics, self-regulated learning and education.
- Access to rich, already collected longitudinal datasets, alongside opportunities to contribute to new data collections
- In-depth training in longitudinal modelling, survival analysis, and explainable machine learning, plus guidance in scientific publishing and in developing your own research profile.
- Funding for presenting your work at national and international conferences (e.g., GEBF, EARLI, AERA).
- Integration into the LEAD Graduate School & Research Network and into the SRL-Hub of the Hector Research Institute.
Requirements
We are looking for a candidate with a strong quantitative background, a genuine interest in how students learn, and motivation to contribute to high-quality scientific publications. Specifically, we expect:
- An excellent academic degree (Master's or equivalent) in Psychology, Empirical Educational Research, Educational Science, Data Science, Statistics, Economics, Learning Sciences, or a related field.
- A strong interest in self-regulated learning, motivation, and achievement emotions in authentic educational settings.
- Solid training in quantitative methods and the willingness to acquire advanced longitudinal and machine-learning methods.
- Programming skills in R (or a demonstrated ability to acquire them quickly).
- An interest in working with large, real-world data from digital learning environments combined with repeated survey measures.
- A willingness to engage in interdisciplinary collaboration and teamwork.
- Proficiency in English as the working language of an international research team, the ability to work independently, and a high level of personal commitment.
- A commitment to continuous professional development in line with the project’s requirements.
In addition, the following qualifications would be considered an asset:
- Experience with longitudinal data and/or machine learning and model interpretation.
- Experience with educational log or trace data, learning analytics, or educational data mining.
- German language skills, helpful for the German-language course materials and survey instruments, but not a requirement.
Application Documents
- A motivation letter
- CV
- Transcripts
- And the names of two academic referees.
Check also:
2026 Fully Funded Humboldt Research Fellowship
2026 Eutopia PhD Co-tutelle Call
Application Deadline
September 8, 2026How To Apply
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Please submit your complete and compelling application as a single PDF document. Your application should include the Application Document.. Reference "PhD TRACE" in the subject line of your email. Send your application to [email protected] by 08.09.2026. Interviews are scheduled for September 22, 2026.
For more information, kindly visit the University of Tübingen webpage.
