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Colin Zarzycki

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Postdoctoral Scholar in Global AI/ML Modeling and Scenario Generation The Pennsylvania State University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

DOE-funded HyperFORMANCE project; full-time postdoctoral scholar position with continuation dependent on university need, performance, and/or availability of funding.

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Country

United States

University

Pennsylvania State University

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Keywords

Computer Science
Environmental Science
Artificial Intelligence
Earth Science
Uncertainty Analysis
Hydrometeorology
High Performance Computing
Climate Extremes
Statistics
Physics
ML

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About this position

The Department of Earth and Mineral Sciences at The Pennsylvania State University is seeking a postdoctoral scholar to contribute to the DOE-funded HyperFORMANCE project. The position is based in a multi-institutional research effort focused on developing global AI/ML Earth system emulators and regional downscaling methods for generating physically credible extreme weather scenarios.

Working under the supervision of Prof. Colin Zarzycki, the postdoc will help evaluate how global AI/ML emulators reproduce extreme weather features and where physics-based models remain essential. The project combines AI/ML methods, physics-based simulations, existing model archives, and certified emulation to build libraries of decision-relevant extreme events for downstream risk assessment.

The scholar will develop and apply machine learning clustering techniques to distill large event libraries into representative scenario sets and event archetypes. They will also generate large ensembles of spatially coherent and temporally compounded hazard scenarios at testbed-relevant scales, supporting applications in water and energy system risk analysis.

Research activities include applying global weather and climate emulators, performing process-oriented diagnostics on extreme precipitation and major storm systems, comparing emulator outputs against physics-based benchmarks and observations, and using regional downscaling tools to create km-scale meteorological fields. The role also involves collaboration with hydrologic, energy, and urban impacts teams, plus participation in workshops, coordination meetings, conference presentations, and peer-reviewed publications.

Funding details

DOE-funded HyperFORMANCE project; full-time postdoctoral scholar position with continuation dependent on university need, performance, and/or availability of funding.

What's required

A Ph.D. in atmospheric science, Earth science, computer science, physics, applied mathematics, or a closely related field must be conferred prior to the start date. Applicants should have demonstrated experience with scientific Python programming (NumPy, Xarray, Pandas, Scikit-learn), experience with machine learning techniques such as clustering, classification, dimensionality reduction, or emulation, familiarity with large climate or weather datasets and analysis of extreme events, experience in UNIX and high-performance computing environments, strong written and verbal communication skills, and the ability to work collaboratively in a multi-institutional team. Preferred qualifications include experience with physics-based and/or data-driven climate/weather models, familiarity with feature-based extreme event detection and tracking, knowledge of tropical cyclones, atmospheric rivers, mid-latitude storms and/or other synoptic-scale weather extremes, and interest in uncertainty quantification and ensemble modeling.

How to apply

Apply through Penn State Workday as an external applicant unless you are a current Penn State employee or student, in which case apply internally through Workday. Submit a CV, a 1-2 page statement of research interests and relevant experience, and contact information for three professional references.

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Professors

Prof. at The Pennsylvania State University

University Name
Country flag

United States

Research Interests

Artificial Intelligence

Statistics

Computer Science

Earth Science

High Performance Computing