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Scientist in Terrestrial Model-Data Integration

Date: Jun 18, 2022

Location: Oak Ridge, TN, US, 37830

Company: Oak Ridge National Laboratory

Requisition Id 6657 


The Earth Systems Science section (ESS) within the Environmental Sciences Division (ESD),, at Oak Ridge National Laboratory (ORNL),, is seeking a scientist to advance the integration of observations and experiments into Earth system models across multiple scales. The successful candidate will demonstrate strong multidisciplinary expertise and quantitative skills. Their research will improve the predictability of terrestrial processes and feedbacks in Earth system models through improved model benchmarking, parameterization and structure.  Possible applications include assimilating remote sensing datasets (e.g. solar-induced fluorescence or other vegetation indices), eddy covariance datasets, and information from ecosystem manipulation experiments into land-surface models. 


ESD is an interdisciplinary research and development organization with more than 60 years of achievement in local, regional, national, and international environmental research. Our vision is to expand scientific knowledge and develop innovative strategies and technologies that will strengthen the nation’s leadership in creating solutions to help sustain the Earth’s natural resources. Our scientists conduct research, develop technology, and perform analyses to understand and assess responses of environmental systems at the environment-human interface and the consequences of alternative energy and environmental strategies. 


The ESS section is world-renowned for large-scale experimental manipulations and is currently leading the US DOE flagship ‘Spruce and Peatland Responses Under Changing Environments’ (SPRUCE) field experiment ( ESD staff also lead the Next Generation Ecosystem Experiment (NGEE) Arctic project (, and we are an integral partner in the NGEE Tropics research project ( We also lead the Critical Interfaces Science Focus Area (CI-SFA,, which investigates the role of hydrology on the transformation of redox-sensitive elements, such as mercury, in a flowing stream system. ESS staff also lead the development of multiple land system components in the US DOE Energy Exascale Earth System Model (E3SM, 


Major Duties/Responsibilities: 

The selected candidate will work with a diverse team of researchers seeking to advance our scientific understanding and simulation capability of terrestrial carbon, water and nutrient cycles and their responses to multiple interacting climate and anthropogenic forcing factors. Identification of model biases through model-data integration and development of improved process algorithms is a primary goal of this team. You will utilize your strong mathematical skills to develop model-data integration methods using machine learning, and will develop new functions and representations of ecological processes in models over a variety of spatial and temporal scales. It is expected you will publish your findings in top-quality journals, and you will have the opportunity to participate in the generation of novel research concepts. 


Qualifications Required 

  • A minimum of five years of post-Ph.D. experience 
  • Ph.D. in a discipline relevant to terrestrial ecosystems (e.g., ecology, engineering, atmospheric science, computational science)  
  • Experience with modeling the terrestrial cycling of carbon, energy and nutrients
  • Ability to design and implement simulation models and advanced statistical models, develop and apply machine learning methods to conduct multi-objective optimization, and assess uncertainty in model predictions, using common scientific programming tools (e.g. FORTRAN, C#, R, Matlab, GIS)  
  • Experience with high-performance computing environments
  • Exceptional interpersonal skills, an ability to work as a part of a team, and be comfortable in a multi-disciplinary environment 
  • Excellent oral and written communication skills and a strong record of publication in high- quality, peer-reviewed, international journals 

At a minimum, we request that applicants include an updated CV and list of references as part of the application packet. 



This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

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ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.

Nearest Major Market: Knoxville