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Oak Ridge National Laboratory 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.


We are seeking a Postdoctoral Research Associate who will support the Computational Earth Sciences Group (CESG) in the Computational Sciences and Engineering Division (CSED), Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL) in Computational Ecohydrology. 


The selected candidate will develop and apply mathematical theory, models, and artificial intelligence (AI)/machine learning (ML) methods to the investigation and simulation of plant carbon and water interactions on accelerator-based supercomputing platforms (e.g., Summit, Frontier, Aurora, and Perlmutter) and conduct simulations and analysis to improve predictions associated with the integrative water cycle and water cycle extremes. CSED focuses on transdisciplinary computational science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut-science outcomes.



The CESG is focused on the conduct of world-class research and development in Earth system modeling, model-data integration, large scale data analytics and machine learning, and model benchmarking at DOE’s Leadership Computing Facilities (LCFs) and its National Energy Research Scientific Computing Center (NERSC). The CESG has specific strengths in numerical methods, simulation, and analysis focused on terrestrial hydrology and biogeochemistry, atmospheric and ocean dynamics, aerosols, regional climate, ice sheets and sea level rise, and the global carbon cycle.


Major Duties/Responsibilities: 

  • Design and implement algorithms for AI/ML methods for hybrid process-/machine learning-based modeling and data analytics on unique hybrid (CPU/GPU) supercomputing architectures
  • Conduct simulations and analyses of plant and soil ecohydrology that connect plant community structure, hydrodynamics, nutrients, and physiology, along with soil composition, biogeochemistry, and physics, to the global water cycle when coupled with other Earth system model components on various high performance computing platforms
  • Work with the research community to design and develop model evaluation metrics and to synthesize benchmark datasets for model evaluation
  • Collaborate with a diverse team of Earth system and computational scientists, both within CESG and across DOE Labs, partner universities, and other federal agency sponsors
  • Publish research in peer-reviewed journals and agency reports, and present results at national and international conferences


Basic Qualifications:

  • A PhD in Computational Science, Hydrological/Hydrodynamics/Hydraulics engineering, Ecosystem Ecology, Applied Mathematics, Geography, Earth System Science, or a related field completed within the last 5 years
  • Experience in model development, simulation, and/or analysis


Preferred Qualifications:

  • Previous research experience with land surface models (e.g., ELM, CLM), terrestrial ecosystem modules (e.g., FATES, ED), soil biogeochemistry modules (e.g., CTC, ECA, FUN), and simulation protocols (e.g., AMIP, CMIP6, C4MIP, LUMIP, LS3MIP)
  • Knowledge of land-related observational data from in situ measurements and remote sensing platforms (e.g., Ameriflux, FLUXNET, AVIRIS-NG, MODIS, GEDI).
  • Experience with FORTRAN, C/C++, and Python languages and with Linux, Git, and LaTeX
  • Familiarity and parallel programming experience with MPI, OpenMP, OpenACC, CUDA, and performance-portable programming models such as Kokkos, Legion, and HPX.
  • Knowledge of commonly used data file formats and conventions (e.g., CF, netCDF, HDF)
  • Experience with high performance computing, advanced statistical and machine learning methods, and visual data analytics
  • Knowledge of terrestrial ecosystem processes, land–atmosphere interactions, hydrological processes, and terrestrial–aquatic processes and their representations in ESMs
  • Ability to report regular progress and publicize results through contributions to manuscripts, reports, and conference presentationsExcellent 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


Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to with the position title and number referenced in the subject line.


Instructions to upload documents to your candidate profile:

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  • Under the My Documents section, select Add a Document


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.


Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.

For more information about our benefits, working here, and living here, visit the “About” tab at




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.