Postdoctoral Research Associate - Urban Earth System Modeling

Pacific Northwest National Laboratory; San Juan (PR); On-site; USD 69,000 - 119,000; Full time

Benefits offered by this job

Medical insurance

Pension plan

Tuition assistance

Relocation

Job summary

Pacific Northwest National Laboratory (PNNL) seeks a postdoctoral research associate to advance urban evolution representation in Earth system models and analyze satellite datasets globally. You will generate ensembles of biophysical parameters for urban areas and incorporate them into DOE’s E3SM to explore sensitivity of meteorological states across scales.

Applicants should have a PhD in Earth/Atmospheric sciences or related fields and strong skills in statistics, HPC, and machine learning.

Qualifications

• PhD within the past five years or within the next eight months.
• Experience with Earth system modeling and statistics.
• Familiar with HPC and satellite data processing.
• Experience with CESM/E3SM or similar models.
• Ability to modify model source code and develop new capabilities.

Responsibilities

• Improve urban evolution representation in Earth system models.
• Run global-scale analyses of satellite data to create ensembles for urban areas.
• Integrate datasets into DOE's E3SM and run sensitivity experiments.
• Apply machine learning to time-series forecasting and remote sensing.

Skills

Statistical analysis

Machine learning

Urban-scale modeling

Satellite remote sensing

Earth system modeling

Critical thinking

Education

PhD in Earth Sciences/Atmospheric Sciences/Environmental Science

Tools

Python

Fortran

NCL

GDAL

Earth Engine (JavaScript)

R

Job description

Pacific Northwest National Laboratory (PNNL) seeks a postdoctoral research associate to advance urban evolution representation in Earth system models and analyze satellite datasets globally. You will generate ensembles of biophysical parameters for urban areas and incorporate them into DOE’s E3SM to explore sensitivity of meteorological states across scales.

Applicants should have a PhD in Earth/Atmospheric sciences or related fields and strong skills in statistics, HPC, and machine learning.