Postdoctoral Researcher (m/f/d): Drivers and statistics of accelerating extreme weather trends

Tasks

• Investigate feedback mechanisms and processes behind acceleration in extreme weather trends
• Design targeted climate model experiments and analyse large ensembles to test conditions under which tail-specific feedbacks are triggered
• Apply explainable AI (XAI) and other advanced statistical methods to uncover non-linear interactions between physical drivers of extremes
• Evaluate how well climate models represent these tail processes against observations and reanalysis
• Investigate drivers, statistics and impacts of record-breaking events in current and future climates, in collaboration with the other group members
• Publish in leading journals, present at international conferences
• Help organise group events
• Co-supervise PhD students

Profile

Essential

• PhD in climate science, atmospheric science, physics, geosciences or a related field
• Solid knowledge of atmospheric dynamics and/or land–atmosphere processes and of climate extremes
• Experience with analysing climate model simulations and observational or reanalysis data
• Programming skills (e.g. Python, R) and experience with statistical analysis of large datasets
• Evidence of scientific productivity, e.g. peer-reviewed publications
• Excellent English skills, and the ability to work independently and collaboratively

Advantageous

• Experience running or configuring climate model experiments
• Experience with explainable AI, machine learning or causal inference methods in the Earth sciences
• Knowledge of extreme value theory, tail statistics or storyline approaches
• Experience with compound event detection and statistics
• Experience with extreme weather attribution methods
• Experience with supervision or teaching

Our offer

This full-time or part-time position with at least 34 hours/week will begin on the 1st of January, 2027, though some flexibility in start date is possible. The term is three years, with the option of an extension. Renumeration will follow the public service pay scale (TVöD Bund ) up to paygroup 13, according to the candidate’s qualifications and experience. You are entitled to an annual bonus, 31 days' holiday and time off on 24th and 31st December. We also offer attractive, family-friendly flexi-time and remote-working arrangements. A company pension scheme (VBL), an employer subsidy for public transport, the opportunity for further training, and language and health courses complete our offer.

The Max Planck Society is committed to employing more individuals with disabilities and especially encourages them to apply. We are also committed to encouraging diversity and actively challenging biases based on gender, nationality, ethnicity, sexual orientation, religion and other components of identity. We were honored with the TOTAL E-QUALITY award for the first time in 2023 for our commitment.

The Max Planck Society supports the compatibility of family and career and is certified according to the "berufundfamilie" (“job and family”) audit.

Your application should include:

• A cover letter
• A CV of no more than 3 pages
• A summary of research interests with max. 2 pages
• A list of at most 10 scientific, peer-reviewed publications related to the position
• Contacts of two referees
• Any relevant certificates

Position remains open until filled.

About us

The Max Planck Institute of Geoanthropology (MPI-GEA) was founded in summer 2022 and is a dynamically growing, highly-interdisciplinary and international research institution. The research focuses on modeling and analyzing the interrelationships between biophysical and human-made systems, looking from the deep past to the future. The institute examines how humanity has driven the emergence of the Anthropocene – the period in which human activities began significantly impacting our planet’s climate and ecosystems – and identifying potential intervention points towards a more sustainable future.

The Carl Zeiss Stiftung Independent Research Group on High-End Climate Risks (CZS-HECR) at MPI-GEA works towards an end-to-end understanding of worst-case climate outcomes, from unprecedented and compounding extremes to their societal impacts. The group combines fundamental physical process understanding rooted in climate physics and Earth System analyses, targeted climate model experiments, advanced statistics, including machine-learning- and explainable AI to deliver usable climate risk estimates under current and future climates for core societal sectors such as health, food, energy and finance.

Contact

Dr. Kai Kornhuber

Email:

Max-Planck-Institute for the Science of Human
Kahlaische Straße 10
07745 Jena
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