Research Associate / Post‑Doc (m/f/d, E13 TV-L, 100%, 4 years)

Bewerbungsfrist:

At the Institute of Education, University of Tübingen, two positions in educational data science and machine learning in education will be filled. The positions are funded through a Momentum grant from the VolkswagenStiftung and are embedded in the research group Teaching and Learning with Educational Technology (Prof. Dr. Andreas Lachner). The research hub focuses on developing AI‑based adaptive teaching systems that are evidence‑based and ready for school practice.

The projects combine expertise from machine learning, data science and education, drawing on large‑scale authentic data to produce robust and generalisable findings. Teachers, students and school administrators are involved in a co‑design process to ensure practical, scalable solutions.

The two positions serve complementary roles: one focuses on applying machine‑learning models to design generative AI‑powered adaptive systems, the other centres on educational data science, analysing longitudinal data and data collected during the project. Computational modelling experience is beneficial.

What we offer

A four‑year contract remunerated according to E13 TV‑L (including visa support through the Welcome Center of the University of Tübingen).
Collaboration in an international, interdisciplinary environment linked 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.
Integration into a motivated research team passionate about teaching and learning with digital media.

What you bring – Position with a Focus on Data Science

A master’s equivalent degree with above‑average grades and a relevant PhD (e.g., in cognitive science, data science, learning analytics or a related field with a strong focus on educational contexts).
Strong methodological research expertise, particularly in computational modelling and in analysing and evaluating complex, large‑scale, non‑structured datasets.
Experience 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 – Position with a Focus on Machine Learning

A master’s equivalent degree with above‑average grades and a relevant 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 and in 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 – both Positions

International peer‑reviewed publications and active participation in professional conferences.
Promotion and support of early‑career researchers in the group.
Engagement within the research group and institute.
Knowledge of digital educational technologies in teaching and learning contexts.
Excellent analytical skills and independence in work.
Strong organisational and communication skills.
Confidence in oral and written English.
Willingness to learn 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.

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Universität Tübingen | Tübingen Center for Digital Education (TüCeDE)