Postdoctoral Research Associate - Peatland Modeling

Overview

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 experiment and other DOE-supported observational networks.

Major Duties/Responsibilities

• 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 data.
• 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.

Basic Qualifications

• 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.

Preferred Qualifications

• Experience with the land model in the Energy 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.

Special Requirements

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 up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.