Postdoc: Urban Earth System Modeling

Pacific Northwest National Laboratory; Columbia (SC); On-site; USD 69,000 - 119,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Flexible spending accounts

Tuition assistance

Relocation assistance

Backup childcare

Job summary

Pacific Northwest National Laboratory seeks a postdoctoral research associate to improve urban evolution representation in Earth system models and to analyze satellite observations for ensemble parameter generation. The role involves integrating data into E3SM and conducting sensitivity experiments across scales.

Ideal candidates have PhD in a relevant field, experience with high-performance computing, geospatial tools, and ML for time-series and remote sensing applications.

Qualifications

• PhD awarded within the past five years or within the next eight months.
• Strong background in earth sciences or related fields and HPC familiarity.
• Experience with time-series analysis, remote sensing, and ML methods.

Responsibilities

• Improve representation of urban evolution in Earth system models.
• Perform global analyses of satellite observations to create ensembles of urban parameters.
• Incorporate datasets into DOE E3SM for sensitivity experiments.
• Run experiments to study urban input effects on meteorological states.

Skills

High-performance computing

Earth system modeling

Statistical analysis

Machine learning

Time-series forecasting

Earth observation

Satellite remote sensing

Google Earth Engine

Education

PhD in Earth Sciences or related field

Tools

GDAL

Python

JavaScript for Earth Engine

R

Earth system modeling codes (CESM / E3SM)

Job description

Pacific Northwest National Laboratory seeks a postdoctoral research associate to improve urban evolution representation in Earth system models and to analyze satellite observations for ensemble parameter generation. The role involves integrating data into E3SM and conducting sensitivity experiments across scales.

Ideal candidates have PhD in a relevant field, experience with high-performance computing, geospatial tools, and ML for time-series and remote sensing applications.