PhD position in Bayesian hierarchical modeling for climate reconstructionFull PhD

The University of Wuppertal (Germany) invites applications for a PhD position (Research Assistant) in the group of Prof. Peter Zaspel, starting March 1, 2026. The position is part of the DFG-funded research project ICEBAY, which focuses on Bayesian hierarchical modeling and probabilistic inference for temperature reconstruction by combining borehole thermometry and ice-core data. The PhD project involves interdisciplinary research at the interface of computer science and mathematics and addresses a complex, coupled inverse problem with explicit uncertainty quantification.

Research tasks
The successful candidate will work on interdisciplinary research at the interface of computer science and mathematics with applications in climate reconstruction. A central aspect of the position is the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data. The candidate will collaborate in an international research team on related topics in probabilistic modeling, uncertainty quantification, and high-performance computing, with applications in the natural and engineering sciences. The position also includes teaching duties (1 semester hour per week) as well as the supervision of term papers and theses.

Required qualifications
Applicants must hold a completed Master’s degree (or equivalent) in a relevant discipline such as computer science, mathematics, physics, or data science. They should have strong analytical skills related to statistics, machine learning, and/or numerical mathematics, as well as an excellent command of a programming language, preferably Python or C/C++. The candidate should have an interest in modeling and solving a complex, coupled inverse problem in an interdisciplinary application. Ideally, applicants have experience in Bayesian inference or Bayesian hierarchical modeling. A good command of English, the working language within the team, is required. We are looking for a competent, proactive personality with commitment and motivation, the ability to work independently, and enjoyment of teaching.

As part of the application process, candidates are required to complete a scientific programming task in the subject area of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bayesian-inference-for-climate-reconstruction

Employment conditions
This is a qualification position in the sense of the German Academic Fixed-Term Contract Act (WissZeitVG) and serves to support a doctoral program. The position is full-time (part-time employment is possible), initially limited to up to three years, with the possibility of extension for the completion of the doctorate within the legal framework. The salary is paid according to TV-L E13.

Application
The application deadline is January 19, 2026. Applications must include a motivation letter, CV, proof of successful graduation, relevant certificates or references, and (if available) a Bachelor’s or Master’s thesis, as well as the completed scientific programming task. Applications are submitted via the University of Wuppertal’s online application portal https://stellenausschreibungen.uni-wuppertal.de under reference number 25354.

For further information, please contact
Prof. Dr. Peter Zaspel
zaspel@uni-wuppertal.de