Postdoc​/Research Scientist – AI Weather Forecasting

The University of Chicago’s Human-centered Weather Forecasting (HCF) and AI for Climate Initiative invite applications for multiple postdoctoral fellow and research scientist positions to work at the intersection of AI and human-centered weather forecasting. The researchers will join Project Cirrus, an interdisciplinary, multi-institutional team led by Professors Pedram Hassanzadeh, Tiffany Shaw, and Amir Jina, and Dr. Katie Kowal at the University of Chicago and Professor Bill Boos at UC Berkeley.

This project builds on HCF’s recent success in benchmarking, developing, and generating AI forecasts for the Indian monsoon onset, which were disseminated to 38 million farmers in India by the Ministry of Agriculture and Farmers’ Welfare. Project Cirrus aims to bridge the gap between AI advances in weather and subseasonal-to-seasonal forecasting and their practical usefulness for decision-makers in developing regions, with a focus on the tropics.

The project leverages advanced tools from scientific machine learning, knowledge of atmospheric dynamics, new observations, and close connections with national meteorological services, as well as several leading weather forecasting centers and tech companies.

Broadly, the topics of interest include:

In addition to being part of the dynamic HCF and AICE communities, these researchers will benefit from participating in major activities around AI and climate at the University of Chicago, organized by the Data Science Institute, the Institute for Climate and Sustainable Growth, and the AI+Science Initiative. The researchers will also have the opportunity to work on the international efforts of the Development Innovation Lab (DIL) to expand access to weather forecasts in low- and middle-income countries.

• Completion of a PhD in Climate Science, Atmospheric Science, Agrometeorology, Physical Oceanography, Applied and Computational Mathematics, Physics, Engineering, or a related field at the time of the appointment;
• Strong programming and numerical skills;
• Experience with high-performance computing and analysis of large datasets;
• Ability to work both independently and as part of a multidisciplinary team;
• Ability to work in a fast-paced environment;
• Strong communication skills.

• Expertise in weather forecasting or climate modeling/dynamics;
• Familiarity with theoretical and practical aspects of scientific deep learning;
• Experience working with observational data, such as remote sensing measurements of precipitation and soil moisture, as well as ground-based measurements;
• Experience with AI weather models.

These positions are benefits-eligible, and information regarding benefits can be found here.

Interested candidates should send:

Please send these materials as a single PDF file to Mauricio Ortiz-Riomalo (ortizriomalo) with the subject line “Application:
Cirrus”. Applications will be reviewed on a rolling basis and accepted until
January 15, 2026. Note that some of our team members will be attending AGU and AMS meetings. They will be happy to meet and answer any questions. Contact katiekowal.

The start date can be flexible but should be before March 1, 2026. Depending on the applicant’s background and interests, the appointment will be made at the Department of Geophysical Sciences or the Data Science Institute.

Outstanding applicants with more than 3 years of postdoc experience will be considered for appointment as research scientists.