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Max Planck Institute of Geoanthropology

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Postdoctoral Researcher in Usable Extreme Weather Projections at Impact-Relevant Scales Max Planck Institute of Geoanthropology in Germany

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full-time or part-time postdoctoral position for three years with the option of extension. Salary follows the public service pay scale (TVöD Bund) up to pay group 13 depending on qualifications and experience. Benefits include annual bonus, 31 days' holiday, flexitime, remote working, pension scheme, public transport subsidy, and training/language/health courses.

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Country

Germany

University

Max Planck Institute of Geoanthropology

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Keywords

Computer Science
Environmental Science
Mathematics
Climate Science
Earth Science
Python Programming
Statistics
Severe Weather
Physics

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About this position

Postdoctoral Researcher (m/f/d): Usable Extreme Weather Projections at Impact-Relevant Scales at the Max Planck Institute of Geoanthropology (MPI-GEA), Jena, Germany.

This postdoctoral opening sits in the Carl Zeiss Stiftung Independent Research Group on High-End Climate Risks (CZS-HECR), which studies worst-case climate outcomes, unprecedented and compound extremes, and their societal impacts. The project combines climate physics, Earth system analysis, targeted climate model experiments, advanced statistics, machine learning, explainable AI, and impact-relevant climate risk estimation for sectors such as health, food, energy, and finance.

Research tasks include identifying and quantifying biases in impact-relevant trends in state-of-the-art climate models (e.g. CMIP6/7, large ensembles, km-scale models), developing AI/ML-driven downscaling approaches for extreme and compound weather events, and designing physics-informed bias-adjustment methods for hazard distribution tails. The role also includes publishing in leading journals, presenting at conferences, contributing to workshops and symposia, co-supervising PhD students, and helping develop a real-time online tool.

Eligibility highlights: a PhD in climate, physics, mathematics, data science, or a related field; experience with climate model output, reanalysis and observational climate data, and large gridded datasets; strong Python programming skills; experience with causality tools, AI and/or machine-learning methods; a strong publication record; and excellent English communication skills. Helpful extras include deep learning for downscaling or bias adjustment, extreme value statistics, compound event detection, high-resolution climate simulations, HPC experience, and impact-oriented applications.

The position is full-time or part-time (at least 34 hours/week), starts on 1 January 2027 with some flexibility, and runs for three years with possible extension. Salary follows TVöD Bund up to pay group 13, with additional benefits such as annual bonus, holiday entitlement, flexitime, remote work, pension, transport subsidy, and training/health/language courses.

Apply via the portal and submit a cover letter, CV (max 3 pages), research interests summary (max 2 pages), up to 10 relevant peer-reviewed publications, two referees, and relevant certificates. The position remains open until filled.

Funding details

Full-time or part-time postdoctoral position for three years with the option of extension. Salary follows the public service pay scale (TVöD Bund) up to pay group 13 depending on qualifications and experience. Benefits include annual bonus, 31 days' holiday, flexitime, remote working, pension scheme, public transport subsidy, and training/language/health courses.

What's required

PhD in climate, physics, math, data science, or a related field; experience with climate model output, reanalysis and observational climate data, and large gridded datasets; strong Python programming skills; experience with causality tools, AI and/or machine-learning methods; a track record of peer-reviewed publications appropriate to career stage; excellent English communication skills; ability to work independently and in a team. Advantageous: deep learning for downscaling or bias adjustment, extreme value statistics, compound event detection, high-resolution climate simulations, HPC environments, impact-relevant applications, co-supervising students, and academic teaching.

How to apply

Apply through the application portal and include a cover letter, CV (max 3 pages), summary of research interests (max 2 pages), up to 10 relevant peer-reviewed publications, contacts of two referees, and any relevant certificates. The position remains open until filled.

More information can be found here

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