Andreas Prein

The High-Resolution Weather and Climate Modeling Group at the Institute for Atmospheric and Climate Sciences (IAC), ETH Zürich, is offering a fully funded PhD position focused on severe thunderstorms, mountain meteorology, and climate change. Supported by a Swiss National Science Foundation (SNSF) Ambizione grant, this opportunity is ideal for candidates interested in advancing the understanding of how topography and climate change influence hail and wind gusts in mountain regions. The project partners include MeteoSwiss, Pennsylvania State University, and the European Severe Storms Laboratory, providing strong international collaboration and opportunities for research stays abroad and participation in a dedicated field campaign. The research will leverage high-resolution idealized numerical modeling (using the ICON model) to analyze both observational datasets and climate model data, aiming to identify typical thunderstorm events and systematic changes in thunderstorm environments. The PhD student will derive representative initial setups for numerical models, design and run experiments reflecting the influences of topography and climate change, and collaborate with international partners in data exchange and modeling. The role also includes presenting scientific findings at conferences, communicating results to the broader public, and preparing peer-reviewed articles. Applicants should have a Master’s degree in meteorology, climate science, physics, or a related field, with demonstrated expertise and programming experience in data analysis and visualization. Desired skills include prior experience with severe thunderstorm dynamics or numerical modeling, familiarity with Linux on HPC clusters, proficiency in python, and a strong interest in extreme weather phenomena. ETH Zürich offers a dynamic, inclusive research environment, competitive salary and employment conditions, and support for publishing and presenting at international conferences. ETH Zürich is renowned for its excellence in science and technology, fostering independent thinking and providing an inspiring environment for over 30,000 people from more than 120 countries. The university values diversity, sustainability, and equality of opportunity, ensuring a fair and open environment for all staff and students. Applications are accepted online until March 14, 2026. Required documents include a motivation letter, CV, MSc transcripts, and contact information for three references. For questions regarding the position, contact Dr. Monika Feldmann at [email protected] (no applications by email). For further details and to apply, visit the ETH Zurich job portal.

This postdoctoral position at ETH Zürich focuses on advancing the application of artificial intelligence (AI), large language models (LLMs), and machine learning to extract trustworthy climate information from large-scale geospatial and Earth system datasets. The research is embedded within the NCCR CLIM+ program, which aims to bridge climate science and AI by developing novel methods for climate data analysis, downscaling, and synthesis using foundation models such as Google Earth AI, AlphaEarth, and TerraTorch on a high-performance computing platform. The successful candidate will design, develop, and apply AI/ML methods—including LLMs and foundation models—to extract, synthesize, and reason about climate information from satellite, reanalysis, and climate model datasets. The role involves advanced physics-aware machine learning for kilometer-scale climate process representation, implementing generative AI models for high-resolution climate downscaling, data assimilation, emulation, and post-processing of weather-to-climate predictions. Methods for uncertainty quantification in projections of extreme weather and climate hazards will also be developed. The researcher will work with multimodal Earth system data, including satellite, airborne, in-situ, reanalysis, and high-resolution climate model outputs. Responsibilities include building robust, scalable software tools and data pipelines for processing large geospatial datasets, enabling CLIM+ project partners and the broader research community to leverage AI-driven climate information. Maintaining reproducible research workflows using modern software engineering practices (version control, testing, documentation, containerization) is expected. Original, publishable scientific research generating novel insights at the intersection of AI and climate science is a core component. The researcher will write and submit peer-reviewed journal papers, present at international conferences, and contribute to NCCR CLIM+ reporting and grant proposals. Collaboration with research groups at ETH Zürich (Prein, Knutti, Fischer) and the University of Zurich (Leippold, Vaghefi, Colesanti Senni) is integral to aligning AI development with climate science research questions. Participation in CLIM+ programme activities, workshops, and cross-project initiatives is encouraged, as is contributing to the supervision of students and interns. Applicants must hold a PhD in climate science, atmospheric science, computer science, data science, physics, applied mathematics, remote sensing, or a related field. A strong publication record in AI, machine learning, or Earth system data science is required. Experience with large geospatial datasets, remote sensing, reanalyses, or climate/weather model output is expected. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, or JAX is necessary. Experience with HPC and GPU-accelerated computing, familiarity with foundation models and LLMs, and interest in reproducible workflows and scientific software development are preferred. Candidates should demonstrate an independent, proactive, and collaborative working style with strong communication skills. ETH Zürich offers an exciting interdisciplinary research environment at the forefront of climate science and AI, a collaborative and supportive team culture, strong support for career development, access to state-of-the-art computing infrastructure, and unique large-scale climate and geospatial datasets. Opportunities exist to develop independent research ideas and build a scientific profile. The institution values diversity, sustainability, and provides a modern, inclusive workplace with attractive employment conditions and flexible working arrangements. Applications must be submitted online via the ETH Zurich application portal. Required documents include a letter of motivation, CV with publication list, copies of relevant degree certificates, and contact details of two or three academic references. Applications sent by email or post will not be considered. All applications submitted before 11 May 2026 will be reviewed. For further information, contact Prof. Andreas Prein, Prof. Reto Knutti, or Prof. Markus Leippold (emails provided in the post).

This postdoctoral position at ETH Zürich focuses on advancing the application of artificial intelligence (AI), large language models (LLMs), and machine learning to extract trustworthy climate information from large-scale geospatial and Earth system datasets. The research is embedded within the NCCR CLIM+ program, which aims to bridge climate science and AI by developing novel methods for climate data analysis, downscaling, and synthesis using foundation models such as Google Earth AI, AlphaEarth, and TerraTorch on a high-performance computing platform. The successful candidate will design, develop, and apply AI/ML methods—including LLMs and foundation models—to extract, synthesize, and reason about climate information from satellite, reanalysis, and climate model datasets. The role involves advanced physics-aware machine learning for kilometer-scale climate process representation, implementing generative AI models for high-resolution climate downscaling, data assimilation, emulation, and post-processing of weather-to-climate predictions. Methods for uncertainty quantification in projections of extreme weather and climate hazards will be developed, and the candidate will work with multimodal Earth system data including satellite, airborne, in-situ, reanalysis, and high-resolution climate model outputs. The researcher will build robust, scalable software tools and data pipelines for processing large geospatial datasets, enabling CLIM+ project partners and the broader research community to leverage AI-driven climate information. Maintaining reproducible research workflows using modern software engineering practices (version control, testing, documentation, containerization) is expected. The candidate will conduct original, publishable scientific research generating novel insights at the intersection of AI and climate science, write and submit peer-reviewed journal papers, present at international conferences, and contribute to NCCR CLIM+ reporting and grant proposals. Collaboration is central to this position, with close interaction with research groups at ETH Zürich (Prof. Andreas Prein, Prof. Erich Fischer, Prof. Reto Knutti) and the University of Zurich (Prof. Markus Leippold). Participation in CLIM+ programme activities, workshops, and cross-project initiatives is encouraged, and the candidate may contribute to supervision of students and interns. Applicants must hold a PhD in climate science, atmospheric science, computer science, data science, physics, applied mathematics, remote sensing, or a related field. A strong publication record in AI, machine learning, or Earth system data science is required. Experience with large geospatial datasets, remote sensing, reanalyses, or climate/weather model output is expected. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, or JAX is necessary. Experience with HPC and GPU-accelerated computing, familiarity with foundation models and LLMs, and interest in reproducible workflows and scientific software development are preferred. Candidates should demonstrate an independent, proactive, and collaborative working style with strong communication skills. ETH Zürich offers an exciting interdisciplinary research environment at the forefront of climate science and AI, a collaborative and supportive team culture, strong support for career development, access to state-of-the-art computing infrastructure, and opportunities to develop independent research ideas. The institution values diversity, sustainability, and provides attractive employment conditions and flexible working arrangements. Applications must be submitted online via the ETH Zurich application portal, including a letter of motivation, CV with publication list, copies of relevant degree certificates, and contact details of two or three academic references. Applications sent by email or post will not be considered. The deadline for applications is 11 May 2026. For further information, contact Prof. Andreas Prein ([email protected]), Prof. Reto Knutti ([email protected]), or Prof. Markus Leippold ([email protected]). Please note that questions regarding the position should be directed to these supervisors, but applications must be submitted through the online portal.