Doctoral position in severe thunderstorms, mountains and climate change

Doctoral position in severe thunderstorms, mountains and climate change

ETH Zürich is well known for its excellent education, ground-breaking fundamental research and for implementing its results directly into practice.

The High-Resolution Weather and Climate Modeling Group at the Institute for Atmospheric and Climate Sciences (IAC) is recruiting a PhD student for a Swiss National Science Foundation (SNSF) funded Ambizione grant, starting between May 1st and September 1st. Applications submitted before March 15 will be considered.

This role focuses on idealized, numerical modeling of severe thunderstorms in mountain regions, exploring the effects of topography and climate change on hail and wind gusts. Project partners include Meteo Swiss, Pennsylvania State University, and the European Severe Storms Laboratory. The project includes funding for a visit with project partners abroad, as well as participation in a planned field campaign.

The position will be based in the High-Resolution Weather and Climate Modeling Group under the supervision of Dr. Monika Feldmann and Prof. Andreas Prein at ETH Zürich.

Severe thunderstorms are a major driver of weather-related damages and frequently occur near mountain ranges, where climate change trends are particularly pronounced. The combined effects of mountains and climate change on thunderstorms are poorly understood, as modeling these effects requires very high resolution and long time series of data, making it computationally expensive. By leveraging findings from recent km-scale modeling and exploiting high-resolution idealized modeling of typical cases, the physical drivers behind enhanced climate trends over mountains can be identified and understood.
The funded Ambizione project involves modeling realistic case studies and idealized, general cases; the PhD project focuses on the idealized modeling portion.

The PhD student is expected to carry out independent research and identify physical drivers of severe thunderstorms in mountains using high-resolution idealized modeling.

Specific tasks:

• Analyzing observational datasets to identify typical thunderstorm events
• Analyzing climate model data to identify systematic changes in thunderstorm environments
• Derive a representative, idealized initial setup for the ICON model
• Design and run ICON modeling experiments that reflect the influences of topography and climate change
• Collaborate with international project partners in data exchange and modeling
• Present and communicate scientific findings at conferences and to the broader public
• Prepare peer‑reviewed articles

Required qualifications and skills:

• Master’s degree in meteorology, climate science, physics or equivalent with demonstrated expertise
• Programming experience in data analysis and visualization

Desired qualifications and skills:

• Prior experience with severe thunderstorm dynamics or numerical modeling
• Familiarity working with Linux on HPC clusters
• Programming experience in Python
• Interest in extreme weather phenomena

• A fully funded PhD position at ETH Zürich within an SNSF Ambizione‑funded project
• The opportunity to work on fundamental questions of severe thunderstorms, mountains, and climate change using state‑of‑the‑art modeling
• Hands‑on experience with high‑resolution numerical simulations using ICON on leading HPC systems
• Close supervision in a highly interactive research environment
• Strong international collaboration with national and international partners
• Funding for research stays abroad and participation in a dedicated field campaign
• Support for publishing in peer‑reviewed journals and presenting at international conferences
• Competitive salary and employment conditions according to ETH Zürich regulations
• A dynamic, inclusive research group and an excellent working environment in Zurich

ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity, and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected.

We would like to point out that the pre‑selection is carried out by the responsible recruiters and not by artificial intelligence.

We look forward to receiving your online application until 14.03.2026 with the following documents:

• CV
• MSc transcripts
• Contact information of 3 references

Questions regarding the position should be directed to Dr. Monika Feldmann, [email protected] (no applications).