Postdoc: AI/ML Climate Emulators for Extreme Weather

The Pennsylvania State University; State College (Centre County); On-site; USD 55,000 - 75,000; Full time

Job summary

The Pennsylvania State University’s Department of Earth and Mineral Sciences invites applications for a full-time Postdoctoral Scholar to support the DOE-funded HyperFORMANCE project under Prof. Colin Zarzycki.

The successful candidate will help develop and apply global AI/ML Earth system emulators and regional downscaling to generate large ensembles of physically credible extreme weather scenarios for water and energy risk assessment.

Qualifications

• PhD in atmospheric/earth science, computer science, physics, math or closely related field, conferred before start date.
• Experience with scientific Python (NumPy, Xarray, Pandas, Scikit-learn).
• Experience with ML techniques (clustering, classification, dimensionality reduction, emulation).
• Familiar with large climate/weather datasets and extreme-event analysis.
• Experience in UNIX and high-performance computing environments.
• Strong written and verbal communication and teamwork.

Responsibilities

• Deploy and analyze outputs from global AI/ML weather emulators and multi-decadal simulations.
• Apply diagnostics to evaluate emulator fidelity for extreme precipitation and cyclones.
• Compare AI emulator outputs with physics-based benchmarks and observations.
• Apply regional downscaling tools to generate km-scale meteorological fields for impacts modelling.
• Develop and refine downscaling workflows across testbed regions.
• Identify representative event archetypes and contribute to publications.
• Present results at scientific conferences and collaborate with multi-institution partners.

Skills

Scientific Python

Machine learning

Climate data analysis

Unix / HPC

Effective communication

Education

PhD in atmospheric science or related field

Job description

The Pennsylvania State University’s Department of Earth and Mineral Sciences invites applications for a full-time Postdoctoral Scholar to support the DOE-funded HyperFORMANCE project under Prof. Colin Zarzycki.

The successful candidate will help develop and apply global AI/ML Earth system emulators and regional downscaling to generate large ensembles of physically credible extreme weather scenarios for water and energy risk assessment.