University of Tübingen
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PhD Position in AI in Education: Multimodal Learning Analytics and Adaptive Learning Environments University of Tübingen in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
The position is a 75% TV-L E13 salaried appointment, limited to three years. The post is available as soon as possible. The announcement does not provide a net salary amount or explicitly state tuition coverage.
Deadline
Nov 25, 2026
Country
Germany
University
University of Tübingen
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About this position
The Hector Research Institute of Education Sciences and Psychology at the University of Tübingen, Germany, is offering a three-year, 75% TV-L E13 PhD position in AI in Education, focused on multimodal learning analytics and adaptive learning environments. The position is available as soon as possible, with applications due by November 25, 2026.
The doctoral researcher will join an interdisciplinary team working at the intersection of artificial intelligence, learning analytics, psychology, cognitive science, and educational research. The project investigates how learners regulate attention and learning, including mind wandering, metacognitive monitoring, and self-regulated learning. Using eye tracking, video, audio, digital trace, and other behavioral data, the researcher will develop multimodal machine-learning models that detect and model learner processes in real time.
The work will also explore how AI systems can be integrated into adaptive learning environments to provide personalized support. Responsibilities include designing and conducting empirical studies, developing multimodal AI models, studying mechanisms underlying attention and learning, and contributing to AI-supported educational technologies. The successful candidate will work with Prof. Dr. Babette Bühler, Prof. Dr. Ulrich Trautwein, the Hector Research Institute, and the LEAD Graduate School & Research Network.
Candidates should have an excellent Master's degree or equivalent in Computer Science, Cognitive Science, Statistics, Psychology, Empirical Educational Research, or a related discipline. Programming ability, preferably in Python, and knowledge of machine learning, statistics, and AI methods are expected. Experience with deep learning, computer vision, multimodal learning analytics, or experimental and user studies is advantageous. English proficiency, interdisciplinary teamwork, independence, and strong motivation are required.
The institute offers comprehensive supervision, methodological training, professional development, opportunities for international collaboration and conference participation, publishing support, and integration into the LEAD Graduate School & Research Network. Apply with a motivation letter, CV, and transcripts as one PDF, referencing “PhD AI in Education,” by email to [email protected].
Funding details
The position is a 75% TV-L E13 salaried appointment, limited to three years. The post is available as soon as possible. The announcement does not provide a net salary amount or explicitly state tuition coverage.
What's required
Applicants should hold an excellent Master's degree or equivalent in Computer Science, Cognitive Science, Statistics, Psychology, Empirical Educational Research, or a related field. They should have a strong interest in human-centered AI, adaptive learning systems, educational technologies, machine learning, and AI methods; programming skills, preferably in Python, or the ability and willingness to develop them rapidly; an interest in multimodal data such as eye tracking, video, audio, and log data; English proficiency for working in an international research team; willingness to collaborate interdisciplinarily; independence, personal commitment, and dedication to continuous professional development. Experience with machine learning, deep learning, computer vision, multimodal learning analytics, field studies, experiments, or user studies is an asset.
How to apply
Submit a complete application as a single PDF containing a motivation letter, CV, and transcripts. Reference “PhD AI in Education” and email the application to [email protected] by November 25, 2026.
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Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.