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Postdoctoral Research Associate - Computer Scientist

Requisition Id 7096 

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.
The Computational Earth Sciences Group (CESG) in the Computational Sciences and Engineering Division (CSED) is seeking a Postdoctoral Research Associate in Computer Science. The candidate will develop and apply mathematical theory and models of hydraulics and hydrology for accelerator-based supercomputing platforms (e.g., Summit, Frontier, Aurora, and Perlmutter) and to conduct simulations and analysis for applications, including flood inundation, weather prediction, and Earth system modeling. 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 candidate will be a postdoctoral scientist within the CESG of the Advanced Computing Methods for Physical Sciences Section in CSED. 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 or refactor and implement algorithms for simulation of hydraulics and/or meso- to global-scale hydrology on unique hybrid (CPU/GPU) supercomputing architectures
  • Conduct simulation and performance optimization and tracking of computational kernels of hydrologic models on various high performance computing platforms
  • Collaborate with a diverse team of Earth system and computational scientists, both within the 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 computer Science, Computational Science, Hydraulics, Hydrologic Engineering, Applied Mathematics, Earth System Science, or a related field completed within the last 5 years
  • 2+ years of experience in model development on hybrid CPU/GPU architectures
Preferred Qualifications:
  • Experience with FORTRAN, C/C++, and Python
  • Familiarity and parallel programming experience with MPI, OpenMP, OpenACC, CUDA, including performance-portable programming models such as Kokkos, Legion, and HPX
  • Experience with high performance computing, advanced statistical and machine learning methods, and visual data analytics
  • Strong motivation to conduct cutting-edge Earth system, weather, and flood simulation studies within multi-disciplinary teams
  • Ability to report regular progress and publicize results through contributions to manuscripts, reports, and conference presentations
  • 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
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.
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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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