Postdoctoral Scholar-Global AI/ML Modeling and Scenario Generation
Penn State University · Posted Nov 11, 2026
- University Park, Pennsylvania, United States
- On-site
- Full-time · Staff
Support the DOE-funded HyperFORMANCE project by developing and applying global AI/ML Earth system emulators and regional downscaling techniques to generate large ensembles of physically credible extreme weather scenarios for water and energy system risk assessment.
Responsibilities
- Evaluate where global AI/ML emulators credibly reproduce extreme weather characteristics and where physics-based models remain necessary
- Combine physics-based simulations, existing model archives, and certified AI/ML emulation to build libraries of decision-relevant extreme events
- Develop and apply machine learning clustering techniques to distill large event libraries into representative scenario sets and event archetypes
- Generate large ensembles of spatially coherent, temporally compounded hazard scenarios at testbed-relevant scales
- Work with hydrologic, energy, and urban impacts teams to ensure scenarios are suitable for downstream applications
Requirements
- Ph.D. in atmospheric science, Earth science, computer science, physics, applied mathematics, or closely related field
- Nice to have: physics-based and/or data-driven climate/weather models
- Nice to have: E3SM
- Nice to have: CESM
- Nice to have: SCREAM