Post Doctorate Research Associate - Urban-Resolving Earth System Modeling
pnnlRichland, WA
Post Doctorate Research Associate - Urban-Resolving Earth System Modeling
L5
pnnlRichland, WAtoday
Occupations
Remote Sensing Scientists and TechnologistsAtmospheric and Space ScientistsPhysical Scientists, All OtherIndustries
Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)Other Scientific and Technical Consulting ServicesEnvironmental Consulting ServicesPostdoctoral Research Associate The Earth System Modeling Group at PNNL seeks a postdoctoral research associate to improve representation of urban evolution, or change in urban extent and properties over time, in Earth system models (ESMs). The successful candidate will perform global-scale analyses of satellite observations and satellite-derived datasets to generate ensembles of temporally varying biophysical parameters for urban areas, both historical and for future scenarios. These datasets will then be incorporated into DOE's Energy Exascale Earth System Model (E3SM) to run sensitivity experiments on the role of urban parameter inputs on local to regional meteorological states across scales. Expertise in statistical analysis (particularly machine learning methods) relevant to time-series forecasting, remote sensing, and previous experience running E3SM or other ESMs is desired.
Minimum Qualifications:
Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university.
Preferred Qualifications:
Ph. D. degree in Earth Sciences, Atmospheric Sciences, Meteorology, Physics, Environmental Science, Environment Engineering, Statistics, or a related field. Familiarity with high-performance computing, Earth system modeling, and statistical analysis. Experience with computer languages usually used for modeling and analysis (Fortran, Python, NCL, C++, etc.).Demonstrated expertise in urban-scale modeling and analysis. Demonstrated expertise in satellite remote sensing, especially using Google Earth Engine. Experience with computer languages used for geospatial modeling and analysis (GDAL, Python, Java Script for Earth Engine, R, etc.).Demonstrated experience in using Earth system models like CESM and/or E3SM.Demonstrated experience in modifying the source code of models to develop new capability. Demonstrated experience in advanced statistical analysis and/or machine learning techniques. Knowledge of novel data-model integration techniques. Ability to think critically and pursue original ideas independently.
Apply now
Level
SeniorL5
Location
Richland, WA
Occupation
Remote Sensing Scientists and Technologists
Industry
Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
Posted
today
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