Date: Apr 16, 2022
Location: Oak Ridge, TN, US, 37830-8050
Company: Oak Ridge National Laboratory
Requisition Id: 6702
The Computational Earth Sciences Group (CESG) in the Computational Sciences and Engineering Division (CSED) is seeking a Research Scientist in Computational Ecohydrology. The 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 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 candidate will be a staff 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 management, 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.
- Design and implement algorithms for AI/ML methods for hybrid process-/machine learning-based modeling and data analytics.
- Conduct simulations and analyses of plant and soil ecohydrology that connect plant community structure, hydrodynamics, nutrients, carbon assimilation, and physiology, along with soil composition, biogeochemistry, and physics, to the global water cycle when coupled with other Earth system model (ESM) 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.
- Ph.D. degree in computational science, Earth system science, ecosystem ecology, hydrology, environmental engineering, applied mathematics, geography, or a related field.
- Experience in land or atmosphere model development, simulation, and/or analysis.
- 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.
- Strong motivation to conduct cutting-edge Earth system ecohydrology studies within multi-disciplinary teams.
- Ability to report regular progress and publicize results through contributions to manuscripts, reports, and conference presentations.
- Excellent verbal and written communication skills.
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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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