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Postdoctoral Researcher - Computational Hydrologist or Reactive Transport Modeler

Oak Ridge National Laboratory (ORNL) is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security. The Environmental Sciences Division (ESD) at ORNL is an interdisciplinary research and development organization with more than 60 years of achievements in local, national, and international environmental research. Our vision is to expand scientific knowledge and develop innovative strategies and technologies to help sustain the Earth’s natural resources.
We are seeking a Postdoctoral Research Associate who will support the Watershed Systems Modeling Group in ESD. Specifically, we seek a computational hydrologist or computational watershed scientist to use and help develop next-generation watershed modeling tools for assessing water availability and water quality in a changing climate.
Major Duties/Responsibilities: 
  • Work as part of a multidisciplinary team, using fully distributed models of watershed hydrology and reactive transport running on high-performance computing resources to simulate streamflow, groundwater availability, and nutrient exports in a changing climate
  • A significant focus will be on multidecadal projections in a changing climate
  • Compare results to observations, existing semi-distributed models, and new data-driven machine-learning approaches
  • Contribute to the ongoing development of state-of-the-art multiscale watershed models
Basic Qualifications:
  • A PhD in Hydrology, Geosciences, Engineering, Applied Mathematics, Computational Science or a related field completed within the last 5 years
  • Experience and demonstrated productivity with numerical models of complex phenomena in C/C++ or Fortran is required, as is basic understanding of watershed hydrology. 
Preferred Qualifications:
  • Previous experience with reactive transport modeling or fully distributed integrated surface/subsurface flow models 
  • Experience with machine learning applied to hydrology or other environmental systems
  • Excellent written and oral communication skills
  • Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory 
  • Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs
For additional information please contact Scott Painter (
Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.
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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.
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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.