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University of Chicago

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Postdoctoral/Research Scientist Positions in AI Weather Forecasting and Climate Science at University of Chicago University of Chicago in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

The positions are fully funded with a salary range between $75,000 and $120,000 per year and are benefits-eligible. Additional information about benefits is available on the university's website.

Deadline

Expired

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Country

United States

University

University of Chicago

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Keywords

Computer Science
Data Science
Machine Learning
Environmental Science
Remote Sensing
Mathematics
Climate Science
Atmospheric Science
Computational Science
Earth Science
Physics
Applied Mathematic

About this position

The University of Chicago’s Human-Centered Weather Forecasting (HCF) and AI for Climate Initiative are seeking multiple postdoctoral fellows and research scientists to join Project Cirrus, an interdisciplinary team focused on AI-driven weather forecasting. The project is led by Professors Pedram Hassanzadeh, Tiffany Shaw, Amir Jina, Dr. Katie Kowal (all at University of Chicago), and Professor Bill Boos (UC Berkeley). Project Cirrus aims to bridge the gap between AI advances in weather and subseasonal-to-seasonal forecasting and their practical usefulness for decision-makers, especially in developing regions and the tropics.

Research topics include developing tools to understand AI weather models for forecasting tropical dynamics, creating human-centered benchmarks for decision-making, and improving AI model performance for weather extremes in data-sparse regions. The project leverages advanced scientific machine learning, atmospheric dynamics, new observations, and collaborations with national meteorological services, leading weather centers, and tech companies.

Researchers will benefit from the vibrant academic environment at the University of Chicago, including the Data Science Institute, Institute for Climate and Sustainable Growth, and AI+Science Initiative. There are also opportunities to work with the Development Innovation Lab on expanding weather forecast access in low- and middle-income countries.

Applicants must have a PhD in a relevant field (climate science, atmospheric science, agrometeorology, physical oceanography, applied/computational mathematics, physics, engineering, or related), strong programming and numerical skills, experience with high-performance computing and large datasets, and strong communication skills. Preferred qualifications include expertise in weather forecasting or climate modeling, scientific deep learning, and experience with observational data and AI weather models.

The positions are fully funded, with a salary range of $75,000–$120,000 and full benefits. Applications are accepted until January 1, 2026, and should include a CV (with publications and references) and a 1-page statement of research fit, sent as a single PDF to Mauricio Ortiz-Riomalo ([email protected]) with the subject 'Application: Cirrus'. The start date is flexible but should be before March 1, 2026. Outstanding applicants with more than 3 years of postdoc experience may be considered for research scientist appointments.

The University of Chicago is committed to diversity, equity, and inclusion, and encourages applicants from all backgrounds. For more information, visit the project and university diversity statements linked above.

Funding details

The positions are fully funded with a salary range between $75,000 and $120,000 per year and are benefits-eligible. Additional information about benefits is available on the university's website.

What's required

Applicants must have completed a PhD in Climate Science, Atmospheric Science, Agrometeorology, Physical Oceanography, Applied and Computational Mathematics, Physics, Engineering, or a related field by the time of appointment. Strong programming and numerical skills, experience with high-performance computing and large datasets, and the ability to work independently and in multidisciplinary teams are required. Strong communication skills are essential. Preferred qualifications include expertise in weather forecasting or climate modeling/dynamics, familiarity with scientific deep learning, experience with observational data (e.g., remote sensing, ground-based measurements), and experience with AI weather models.

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Professors

Professor

University Name
Country flag

United States

Research Interests

Climate Science

Statistics

Mathematics

Environmental Science

Physics

Prof.

University Name
Country flag

United States

Research Interests

Climate Science

Climatology

Earth Science

Computer Science

Physics

Prof.

University Name
Country flag

United States

Research Interests

Climate Science

Climatology

Mathematics

Physics

Atmospheric Science

Prof.

University Name
Country flag

United States

Research Interests

Climate Science

Climatology

Atmospheric Science

Mathematics

Environmental Science