Postdoctoral Peatland Modeling Scientist (ELM/AI)

Oak Ridge National Laboratory; Oak Ridge (TN); On-site; USD 65,000 - 90,000; Full time

Job summary

Oak Ridge National Laboratory (ORNL) seeks a Postdoctoral Research Associate to join the Earth Systems Modeling Group and work on the TES SFA. The successful candidate will contribute to the development and evaluation of the ESM land component (ELM and ELM-Peatlands), focusing on nutrient cycling dynamics and coupling to hydrological and ecosystem processes.

The position offers opportunities at the interface of model development, observational data synthesis, and AI/ML methods, with

Qualifications

• PhD in Earth sciences or closely related field, completed or within six months.
• Experience in ecological modelling and/or Land Surface Modelling.
• Experience in HPC environments.
• Programming in Fortran, Python or R.
• Experience manipulating and analyzing large observation data or model outputs.
• Knowledge of terrestrial biogeochemistry and nutrient cycling.
• Strong communication skills

Responsibilities

• Develop, implement, and test nutrient cycling representations in ELM/ELM-Peatlands.
• Evaluate model performance against SPRUCE, AmeriFlux and other data.
• Compile and harmonize multi-source observational datasets for benchmarking.
• Explore AI/ML approaches to improve nutrient-cycling representation and reduce uncertainty.
• Collaborate with ecologists, biogeochemists, modelers and data scientists across ORNL and DOE communities.
• Present research findings at conferences and prepare manuscripts for peer-reviewed publications.

Skills

Ecological modelling

Land Surface Modelling

HPC experience

Fortran/Python/R

Large datasets

Biogeochemistry

Communication skills

Education

PhD in Earth sciences

Job description

Oak Ridge National Laboratory (ORNL) seeks a Postdoctoral Research Associate to join the Earth Systems Modeling Group and work on the TES SFA. The successful candidate will contribute to the development and evaluation of the ESM land component (ELM and ELM-Peatlands), focusing on nutrient cycling dynamics and coupling to hydrological and ecosystem processes.

The position offers opportunities at the interface of model development, observational data synthesis, and AI/ML methods, with