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Babette Bühler

4 months ago

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

Available

Deadline

Expired

Country flag

Country

Germany

University

University of Tübingen

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Keywords

Computer Science
Machine Learning
Education
Psychology
Cognitive Science
Artificial Intelligence
Human-computer Interaction
Computer Vision
Educational Technology
Metacognition
Eye Tracking
Self-regulated Learning
Learning Analytics
Learning Environment
Statistics

About this position

The Hector Research Institute of Education Sciences and Psychology at the University of Tübingen is offering a PhD position in AI in Education, focusing on multimodal learning analytics and adaptive learning environments. This interdisciplinary research opportunity is embedded within a dynamic team at a leading center for empirical educational research, recognized nationally and internationally. The project aims to develop AI systems capable of modeling, assessing, and supporting learners’ attentional, cognitive, and metacognitive processes in real time using multimodal behavioral data such as eye tracking, video recordings, digital trace data, and other behavioral indicators.

The research initiative sits at the intersection of artificial intelligence, learning analytics, psychology, and educational research. A central focus is understanding how learners regulate their attention and learning processes, including mind wandering, metacognitive monitoring, and self-regulated learning. The PhD candidate will design and conduct empirical studies, develop multimodal machine-learning models, investigate mechanisms underlying attention and learning, and contribute to the development of AI-supported educational technologies. The project also explores how multimodal AI systems can be integrated into adaptive learning environments to provide personalized support based on learners’ attentional and self-regulatory needs.

Supervision will be provided by Dr. Babette Bühler (future Tenure-Track Professor for AI in Education), Prof. Dr. Ulrich Trautwein, and Prof. Dr. Peter Gerjets (IWM), with collaboration opportunities at the Hector Research Institute and the LEAD Graduate School & Research Network. The institute offers comprehensive supervision, methodological training, support for interdisciplinary and international collaborations, guidance in scientific publishing, and integration into a motivated research team passionate about education and AI.

Applicants should have an excellent academic degree (Master’s or equivalent) in Computer Science, Cognitive Science, Statistics, Psychology, Empirical Educational Research, or a related field. Required skills include programming (preferably Python), experience with machine learning and statistical methods, proficiency in English, and interest in working with multimodal data. Candidates should demonstrate enthusiasm for interdisciplinary research, ability to work independently, and commitment to professional development. Additional assets include experience with deep learning, computer vision, multimodal learning analytics, and designing empirical studies or user experiments.

The position is funded as an E13 TV-L, 75% contract for three years, including salary and benefits according to German public sector regulations. The University of Tübingen is committed to equal opportunities and diversity, encourages applications from qualified female researchers, and gives preferential consideration to applicants with disabilities if equally qualified. Employment will be administered through the Central Administration of the University of Tübingen.

To apply, submit your complete application (motivation letter, CV, transcripts) as a single PDF referencing 'PhD AI in Education' by July 15, 2026 via email to [email protected]. For further information, contact Dr. Babette Bühler at [email protected]. More details about the institute can be found at www.hib.uni-tuebingen.de.

Funding details

Available

What's required

Applicants must hold an excellent academic degree (Master’s or equivalent) in Computer Science, Cognitive Science, Statistics, Psychology, Empirical Educational Research, or a related field. Required skills include programming (preferably Python), experience with machine learning and statistical methods, proficiency in English, and interest in multimodal data (eye tracking, video, audio, log data). Candidates should demonstrate enthusiasm for interdisciplinary research, ability to work independently, and commitment to professional development. Additional assets include experience with deep learning, computer vision, multimodal learning analytics, and designing empirical studies or user experiments.

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Professors

Professor at University of Tübingen

University Name
Country flag

Germany

Research Interests

Educational Psychology

Educational Technology

Education

Psychology

Eye Tracking

Professor at University of Tübingen

University Name
Country flag

Germany

Research Interests

Statistics

Artificial Intelligence

Self-regulated Learning

Computer Science

Learning Environment