University of Tübingen
2 months ago
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PhD Position in Learning Analytics and Self-Regulated Learning at University of Tübingen University of Tübingen in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
75% TV-L E13 position, limited to three years, funded by the DFG-funded TRACE project. The post includes funding for presenting work at national and international conferences and access to training and supervision; no tuition information is mentioned.
Deadline
Sep 8, 2026
Country
Germany
University
University of Tübingen
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About this position
PhD position (m/f/d) in Learning Analytics and Self-Regulated Learning at the Hector Research Institute of Education Sciences and Psychology, University of Tübingen (Germany).
This is a DFG-funded doctoral position in the project TRACE: Trajectories of Adaptation, Disengagement, and Choice in Authentic Educational Settings. The role is 75% TV-L E13, limited to three years, and starts on 1 January 2027.
The project studies how university students regulate learning across a semester using weekly online retrieval-practice log data, survey measures, and exam records. Research topics include adaptation after feedback, disengagement and re-engagement, and decisions about exam participation. Methods include longitudinal within-person models, discrete-time survival analysis, and explainable machine learning.
Applicants should hold an excellent Master's degree or equivalent in Psychology, Empirical Educational Research, Educational Science, Data Science, Statistics, Economics, Learning Sciences, or a related field. Strong quantitative skills, interest in motivation and achievement emotions, and programming ability in R are expected. Experience with longitudinal data, machine learning, learning analytics, or educational data mining is an advantage. English proficiency is required; German is helpful but not mandatory.
The position offers close supervision, an international research environment, methodological and professional development, access to rich longitudinal datasets, and conference funding. The project is embedded in the SRL-Hub at the Hector Research Institute and linked to the LEAD Graduate School & Research Network.
Apply by 8 September 2026 by sending a single PDF with motivation letter, CV, transcripts, and two academic referees to [email protected]. Use the subject line "PhD TRACE". Interviews are scheduled for 22 September 2026.
Funding details
75% TV-L E13 position, limited to three years, funded by the DFG-funded TRACE project. The post includes funding for presenting work at national and international conferences and access to training and supervision; no tuition information is mentioned.
What's required
Applicants should have an excellent Master's degree 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 is expected, along with solid quantitative training and willingness to learn advanced longitudinal and machine-learning methods. Programming skills in R are required or must be quickly acquired. Experience with longitudinal data, machine learning, model interpretation, educational log/trace data, learning analytics, or educational data mining is an asset. English proficiency is required; German is helpful but not required. Applicants should be able to work independently, collaborate in an interdisciplinary team, and show strong commitment to professional development.
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