PhD / PostDoc (m/f/x)

About us:

The StaBLab is part of the Institute of Statistics at LMU Munich. We provide statistical consulting for each step of the data analysis pipeline for research projects as well as for partners in industry.

We are looking for you:

in Munich

Your tasks and responsibilities:

• Develop Bayesian hierarchical models to account for complex structures of uncertainty in experimental and observational studies
• Support in teaching applied statistics courses such as linear modelling
• Manage research assistants on statistical consulting projects

Your qualifications:

• Hold an excellent master’s degree in statistics or a related field (PostDoc applicants must hold a PhD degree in a related field)
• Bring interest (and ideally experience) in Bayesian inference and meta-research
• Program proficiently in R and / or Python
• Demonstrate strong communication skills in English, with German language proficiency considered an advantage
• Balance long-term research project goals with consulting requests independently
• Willing to work in a team
• Bring an interest in biomedical and meta-research questions and a willingness to work across disciplines

Benefits:

Salary and benefits are in accordance with the German public sector scale (TV-L E13, 100%, 59.000 – 73.000 €, TV-L). The position is initially limited to one year, with a planned extension of up to two additional years.

The office is in Munich, working from home is possible, and working hours are flexible. Successful candidates are encouraged to present their research on national and international conferences.

The position is suitable for disabled persons.

Also possible in a part-time capacity.

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

Contact:

How to apply
Send an E-Mail to Dr. Sabine Hoffmann: kontakt@stablab.stat.uni-muenchen.de with the subject line “Position in Bayesian modelling” and include

• CV
• Academic transcripts (bachelor, master, list of publications)
• If available, academic and / or employment references

Applications are reviewed on a rolling basis; Only shortlisted candidates will be contacted or invited to interview.

Application Deadline: 28.08.2026

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