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Institution Faculty of Psychology and Educational Sciences - Faculty of Psychology and educational Science Chair of Education and Educational Psychology Remuneration group TV-L E13 Full-time / Part-time Part-time (75%) Start date 01.01.2027 (3 years)

About us:

The DFG-funded Collaborative Research Centre SHARP ‘Simulation-based learning in higher education: Advancing research on process diagnostics and personalised interventions’ contributes to theory-building on personalising learning using simulations in higher education. As a joint research context, SHARP focuses on diagnosing and intervening as two highly relevant professional practices in many academic professions.
The subproject P ‘Advancing Person Centred Methods for Research on Simulation-Based Learning in Higher Education’, explores the statistical approach of mixture modeling (e.g., latent profile analysis, latent transition-, growth mixture- and hidden Markov-modeling) as a means for modeling for whom which experimental treatment works best to support simulationbased learning and how to adapt to learners` preconditions. The project is currently looking for a doctoral researcher. The position is located at the Department of Psychology, Chair of Education and Educational Psychology, Professorship for Methods of Empirical Educa-tional Research (Prof. Peter Edelsbrunner), in collabo-ration with the Professorship of Research on Learning and Instruction (Prof. Sarah Hofer) and the Professorship Psychology of Teaching and Learning at the School of Social Sciences and Technology of TUM (Prof. Doris Holzberger).
You can find an overview of all sub-projects and open positions .

We are looking for you:

Doctoral Researcher (m/f/x)

in Munich

Your tasks and responsibilities:

• planning, preparing and conducting methodological and applied research on mixture modelling in simulationbased learning
• conducting systematic reviews, statistical simulation studies, conceptual methodological research, and applied statistical modelling
• analysing data
• contributing to scientific publications.

Your qualifications:

• You have a very good Master´s degree or equivalent in the field of psychology, educational science, applied statistics, data science, or learning sciences.
• You are interested in interdisciplinary collaboration and working in research teams.
• You have very good knowledge of social science research methods including the R software environment, statistical analyses and modelling.
• You interested in planning and conducting studies at the crosssection of quantitative methodology and applied educational research.
• Experiences with mixture modelling and process analyses would be an advantage.
• You have very good written and spoken English skills.

Benefits:

• We offer the opportunity to gain further academic qualifications, particularly to obtain a doctorate in educational psychology, educational research or learning sciences.
• Contributing to the CRC SHARP, you will become part of an interdisciplinary group of researchers working in an excellent research environment to significantly advance higher education theory and practice.
• The CRC provides all its members with tailored support, coaching and supervision, including special support for international researchers.
• You will be paid an attractive salary at the payscale 0.75 FTE of TV-L E13. Your contract will be limited to 3 years.
• Your workplace is centrally located in Munich and easily accessible by public transportation.
• LMU has signed the "Diversity Charter" and is committed to diversity among its employees. We actively promote gender equality.

We welcome applications from women and other groups that are currently underrepresented in the academic system.

People with disabilities who are equally as qualified as other applicants will receive preferential treatment.

Contact:

Your detailed application includes a cover letter, your CV and copies of your transcripts and certificates.
Please submit your application by 19/10/2026 at the latest.
If you have any questions, please contact Prof. Peter Edelsbrunner ().

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