Wissenschaftliche Mitarbeiter/in (100%, TVL-13) Data Science & Machine Learning
Research Associate/ Post-Doc (m/f/d, E13 TV-L, 100%)
Bewerbungsfrist : 08.05.2026
At the Institute of Education, University of Tübingen, two positions as
Research Associate (Post-Doc, m/f/d, E 13 TV-L, 100%, 4 years)
in the area of educational data science and machine learning in education are to be filled as soon as possible.
The positions are funded through a Momentum grant of the VolkswagenStiftung and are embedded in the research group Teaching and Learning with Educational Technology (Prof. Dr. Andreas Lachner) at the Institute of Education. At the heart of the project is the transformation of the re-search group into a trans-disciplinary research hub for AI-based adaptive teaching. The goal is to research and design evidence-based adaptive learning systems and translate them into school practice — systems that provide individualized support and offer all students fair educational opportunities regardless of their background. Artificial intelligence, particularly in the form of large language models (LLMs), is widely regarded as a promising tool in this context. However, a systematic, empirically grounded integration of these technologies into everyday school life is still lacking — and this is precisely where the project intervenes. The project enables a targeted combination of expertise from machine learning, data science, and education with insights from educational practice. Drawing on large-scale data from authentic educational contexts, the project aims to generate robust and generalizable findings. In close collaboration with local and international partners, we establish an interface between educational research, subject-specific didactics, and AI development. A central feature of the approach is its co-design process: teachers, students, and school administrators are actively involved in shaping the systems to ensure practical, effective, and scalable solutions.
The two positions serve complementary but distinct functions within the project. One position focuses on the application of machine learning models for designing and implementing generative AI-powered adaptive systems. The second position centers on educational data science, primarily inVolving the theory-driven analysis of existing longitudinal datasets as well as data collected during the project. Experience in computational modelling is an asset.
The activities of the research group are closely connected to the Tübingen Center for Digital Education (TüCeDE), an interfaculty, interdisciplinary center at the University of Tübingen.
The positions are limited to four years.
What we offer:
- A four-year contract remunerated according to E13 TV-L (if necessary, support with visa application through the Welcome Center of the University of Tübingen)
- Collaboration in an international and interdisciplinary research environment at the University of Tübingen, with close connections to the LEAD Graduate School & Research Network, the Tübingen School of Education, the Tübingen AI Center, and external partners such as the ELLIS Institute Tübingen and the Leibniz‑Institut für Wissensmedien.
- Opportunities for further education and training
- Inclusion in a dynamic team of motivated researchers passionate about teaching and learning with digital media
What you bring for the Position with a Focus on Data Science:
- A master’s equivalent university degree with above average grades and a relevant doctorate/PhD (e.g. in cognitive science, data science, learning analytics, or a related field with a strong focus on educational or learning contexts)
- Strong methodological research expertise, particularly in:
- Computational modeling
- The analysis and evaluation of complex, large scale, and non-structured datasets
- Experience in applying theory-driven approaches to educational data, ideally in learning analytics or digital education settings
- Ability to design, implement, and critically evaluate data science methodologies for research purposes
What you bring for the Position with a Focus on Machine Learning:
- A master’s‑equivalent university degree with above‑average grades and a relevant doctor-ate/PhD (e.g. in machine learning, artificial intelligence, computer science, or a related discipline with an educational focus)
- Strong methodological research expertise in:
- Applying machine learning techniques to educational problems
- Designing, developing, and evaluating AI-based adaptive systems
- Experience with model development, validation, and performance evaluation in applied or research‑oriented settings
- Ability to translate machine learning methods into practical, scalable educational applications
What we expect from you on both Positions:
- International, peer-reviewed publications of research papers and active participation in professional conferences
- Promotion and support of early-career researchers at the research group
- Engagement within the research group and institute
- Knowledge of digital educational technologies in teaching and learning contexts
- Excellent analytical skills and the ability to work independently
- Strong organizational and communication skills
- Confident in oral and written English
- Willingness to familiarize oneself with new areas of work and to participate in regular professional training
Severely disabled applicants will be given preferential consideration if equally qualified.
The University of Tübingen aims to increase the proportion of women in research and teaching and therefore encourages suitably qualified female scientists to apply.
Please submit your application with the usual documents by May 8, 2026, in electronic form (please only one PDF document) to info@tuecede.uni-tuebingen.de . If you have any questions, please con-tact Dr. Iris Backfisch iris.backfisch@uni-tuebingen.de or Prof. Andreas Lachner andreas.lachner@uni-tuebingen.de .
The employment is handled by the Central Administration.