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Johns Hopkins University

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Postdoctoral Scholar in AI & Climate at Johns Hopkins University Johns Hopkins University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

2-year postdoctoral scholar appointment, renewable after year 1 and extensible. Includes conference travel support and professional development support.

Deadline

Sep 10, 2026

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Country

United States

University

Johns Hopkins University

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Keywords

Computer Science
Environmental Science
Mathematics
Artificial Intelligence
Climate Science
Atmospheric Science
Earth Science
Python Programming
Uncertainty Analysis
Extreme Events
Numerical Weather Prediction
Statistics
Emulation
Physics
Applied Mathematic

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About this position

Johns Hopkins University in Baltimore, Maryland is advertising a Postdoctoral Scholar in AI & Climate within the Climate Intelligence Lab led by Prof. Karen McKinnon.

The project focuses on AI-based observational large ensembles, using emulators to develop, validate, and analyze climate and weather models, with an emphasis on low-probability, high-impact extremes and the physical mechanisms behind them. A major theme is uncertainty quantification for AI weather, subseasonal-to-seasonal (S2S), and climate models.

This is an in-person position for 2 years, renewable after year 1, with scope to extend and pursue emerging research problems. The post also includes conference travel and professional development support.

Applicants should hold a PhD in Atmospheric/Climate/Earth Science or in Computer Science, Applied Mathematics, or Statistics. The post specifically asks for strong quantitative skills, climate publications, proficiency in Python, and strong scientific writing.

To apply, email [email protected] with the subject line AI/climate postdoc application, along with a 1-page cover letter, CV, and 3 references. Review begins on September 10, 2026, and the start date window is November 1, 2026 to March 1, 2027.

Funding details

2-year postdoctoral scholar appointment, renewable after year 1 and extensible. Includes conference travel support and professional development support.

What's required

PhD in Atmospheric Science, Climate Science, Earth Science, Computer Science, Applied Mathematics, or Statistics; strong quantitative skills; experience with climate publications; proficiency in Python; and strong scientific writing. The post emphasizes interest in AI/weather/S2S/climate modeling and uncertainty quantification.

How to apply

Email Karen McKinnon with the subject line "AI/climate postdoc application". Include a 1-page cover letter, CV, and 3 references.

More information can be found here

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