Max Planck Institute of Geoanthropology
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Postdoctoral Researcher in Drivers and Statistics of Accelerating Extreme Weather Trends Max Planck Institute of Geoanthropology in Germany
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full-time or part-time postdoctoral position for at least 34 hours/week, starting 2027-01-01 with some flexibility. Initial term is three years with the option of a 2-year extension. Salary follows TVöD Bund up to pay group 13 depending on qualifications and experience, plus annual bonus, 31 days' holiday, pension scheme, public transport subsidy, training, and language/health courses.
Country
Germany
University
Max Planck Institute of Geoanthropology
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About this position
Postdoctoral Researcher in Drivers and Statistics of Accelerating Extreme Weather Trends 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 compounding extremes, and their societal impacts. The project combines climate science, atmospheric science, Earth science, physics, statistics, and computer science methods such as machine learning and explainable AI.
The successful candidate will investigate feedback mechanisms behind accelerating extreme weather trends, design targeted climate model experiments, analyse large ensembles, and evaluate how well climate models represent tail processes against observations and reanalysis. The role also includes studying drivers, statistics, and impacts of record-breaking events in current and future climates, publishing in leading journals, presenting at international conferences, helping organise group events, and co-supervising PhD students.
Eligibility highlights: a PhD in climate science, atmospheric science, physics, geosciences, or a related field; strong knowledge of atmospheric dynamics and/or land–atmosphere processes and climate extremes; experience with climate model simulations and observational/reanalysis data; programming in Python or R; statistical analysis of large datasets; strong publication record; and excellent English.
Desirable experience: climate model experiments, explainable AI, machine learning, causal inference, extreme value theory, tail statistics, storyline approaches, compound event detection, extreme weather attribution, and supervision/teaching.
Funding and terms: full-time or part-time (minimum 34 hours/week), starting 2027-01-01 with some flexibility. The appointment is for 3 years with a possible 2-year extension. Salary follows TVöD Bund up to pay group 13, with annual bonus, 31 days' holiday, pension, public transport subsidy, training, and language/health courses.
How to apply: submit the application via the online portal and upload a cover letter, CV (max 3 pages), research interests summary (max 2 pages), up to 10 relevant peer-reviewed publications, contacts of two referees, and any relevant certificates. The position remains open until filled.
Funding details
Full-time or part-time postdoctoral position for at least 34 hours/week, starting 2027-01-01 with some flexibility. Initial term is three years with the option of a 2-year extension. Salary follows TVöD Bund up to pay group 13 depending on qualifications and experience, plus annual bonus, 31 days' holiday, pension scheme, public transport subsidy, training, and language/health courses.
What's required
PhD in climate science, atmospheric science, physics, geosciences or a related field; solid knowledge of atmospheric dynamics and/or land–atmosphere processes and climate extremes; experience analysing climate model simulations and observational or reanalysis data; programming skills such as Python or R and experience with statistical analysis of large datasets; evidence of scientific productivity such as peer-reviewed publications; excellent English skills; ability to work independently and collaboratively. Advantageous: experience running or configuring climate model experiments, explainable AI, machine learning or causal inference methods in the Earth sciences, extreme value theory, tail statistics, storyline approaches, compound event detection and statistics, extreme weather attribution methods, and supervision or teaching experience.
How to apply
Apply through the online application portal and include a cover letter, CV (max 3 pages), summary of research interests (max 2 pages), list of up to 10 relevant peer-reviewed publications, contacts of two referees, and any relevant certificates.
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