Postdoctoral Research Associate - Coastal Landscape Geospatial Modeling

• Develop, implement, and test new and improved process representations of nutrient (nitrogen and phosphorus) cycling and their coupling to hydrological and ecosystem processes within ELM and ELM-Peatlands.
• Evaluate model performance against observational and experimental datasets, including data from SPRUCE, AmeriFlux towers, and other observational and experimental
• Compile, harmonize, and synthesize multi-source observational datasets (e.g., flux, soil biogeochemistry, plant trait, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification.
• Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI-assisted model calibration, or pattern detection in large observational datasets) to improve nutrient-cycling representation and reduce predictive uncertainty in models.
• Collaborate with an interdisciplinary team of ecologists, biogeochemists, modelers and data scientists across ORNL and the broader DOE E3SM and Environmental System Science communities.
• Present research findings at scientific conferences and prepare manuscripts for peer-reviewed publication.

• A Ph.D. in Earth sciences, environmental sciences, atmospheric sciences, or a closely related field, either already completed or expected to be completed within the next six months.
• Experience in ecological modelling and/or Land Surface Modelling
• Knowledge and experience working in HPC environment.
• Programming experience in Fortran, Python or R
• Experience in manipulating and analyzing large observation data or model outputs
• Working knowledge of terrestrial biogeochemistry and nutrient-cycling processes
• Strong communication skills, * Experience with the land model intheEnergy Exascale Earth Model(E3SM) or Community Earth System Model (CESM)
• Background in peatland, wetland, or high-latitude ecosystem biogeochemistry.
• Experience applying machine-learning or AI methods to environmental data analysis, model calibration, or model-data integration.
• Experience synthesizing multi-source, multi-scale observational datasets.

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The Environmental Sciences Division at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to join the Earth Systems Modeling Group (ESMG) to work on the Terrestrial Ecosystem Science Scientific Focus Area (TES SFA). The successful candidate will contribute to the development and evaluation of the Energy Exascale Earth System Model’s land component (ELM) and its peatland-specific configuration (ELM-Peatlands), with a focus on improving the representation of nutrient cycling dynamics and their coupling to hydrological and ecosystem processes. The position offers the opportunity to work at the interface of model development, observational data synthesis, and emerging AI/ML methods, in close collaboration with researchers from the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment and other DOE-supported observational networks., As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.