Postdoc: Urban Earth System Modeling

Pacific Northwest National Laboratory; United States; On-site; USD 69,000 - 119,000; Full time

Benefits offered by this job

Medical insurance

Pension plan

Tuition assistance

Relocation assistance

Flexible scheduling

Job summary

Pacific Northwest National Laboratory (PNNL) seeks a postdoctoral research associate to advance urban evolution in Earth system models. Analyze satellite observations to build ensembles of urban biophysical parameters and test their impact in DOE’s Energy Exascale Earth System Model (E3SM).

The ideal candidate has a PhD in a related field, experience with time-series analysis, machine learning, and programming in Python, Fortran, or C++. Collaborative, cross-disciplinary work is essential.

Qualifications

• PhD completed within past five years (60 months) or within the next 8 months.
• Experience with high-performance computing and Earth system modeling.
• Proficiency in time-series analysis, machine learning, remote sensing.

Responsibilities

• Improve representation of urban evolution in Earth system models.
• Perform global-scale analyses of satellite data to generate ensembles of urban biophysical parameters.
• Incorporate datasets into DOE’s Energy Exascale Earth System Model (E3SM) for sensitivity experiments.

Skills

Fortran

Python

NCL

C++

Urban-scale modeling

Google Earth Engine

GDAL

JavaScript

Earth system models

CESM/E3SM

Machine learning

Time-series analysis

Education

PhD in Earth Sciences or related field

Tools

Google Earth Engine

GDAL

CESM

E3SM

Fortran

C++

Python

JavaScript

R

Job description

Pacific Northwest National Laboratory (PNNL) seeks a postdoctoral research associate to advance urban evolution in Earth system models. Analyze satellite observations to build ensembles of urban biophysical parameters and test their impact in DOE’s Energy Exascale Earth System Model (E3SM).

The ideal candidate has a PhD in a related field, experience with time-series analysis, machine learning, and programming in Python, Fortran, or C++. Collaborative, cross-disciplinary work is essential.