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Aminu Ma'aruf Nass

4 days ago

PhD/Postdoc in Bayesian Hierarchical Modeling at Ludwig-Maximilians-Universität Ludwig-Maximilians-Universität in Germany

Degree Level

PhD, Postdoc

Field of study

Computer Science

Funding

Full funding available

Deadline

Aug 28, 2026

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Country

Germany

University

Ludwig Maximilian University

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Keywords

Computer Science
Mathematics
Uncertainty Analysis
Hierarchical Modeling
Teaching And Learning
Econometric
Statistics
Statistical Consulting

About this position

Statistisches Beratungslabor (StaBLab) at Ludwig-Maximilians-Universität is hiring for a PhD/Postdoc position focused on Bayesian hierarchical modeling and methods for accounting for complex uncertainty structures.

The successful candidate will support the lab’s work in statistical consulting and teaching. This is a research-oriented opportunity in applied statistics with a strong modeling component, suitable for candidates interested in Bayesian methods, uncertainty quantification, and practical statistical support in an academic environment.

Funding/salary: The post offers a salary of €59,000–€67,000. The position starts as soon as possible.

Eligibility/requirements: The post explicitly targets PhD/Postdoc applicants. No further formal requirements are listed in the post, but a background in statistics, mathematics, or closely related quantitative fields would fit the advertised topic.

Application window: The deadline is 28 August 2026, and applications are reviewed on a rolling basis, so early application is recommended.

Research keywords: Bayesian hierarchical modeling, uncertainty quantification, statistical consulting, teaching, applied statistics.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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