Postdoctoral Associate in Carbon Cycle Modeling

About the Role

The Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado Boulder, in partnership with the NOAA Global Monitoring Laboratory (GML), seeks a Postdoctoral Associate to focus on atmospheric data quality control, analysis, and inverse modeling of the carbon budget for the Congo Basin. This position is part of the Schmidt Sciences Virtual Institute for the Carbon Cycle (VICC) project, Congo Basin Carbon Flux Experiment (Congo-FLEX), aiming to quantify the carbon budget using top-down and bottom-up methodologies. The role involves quantifying and interpreting carbon fluxes using new aircraft vertical profile observations and a regional inverse modeling framework.

Key Responsibilities

• Quantify and interpret carbon fluxes constrained by new aircraft vertical profile observations, primarily using a regional inverse modeling framework (65%). This includes:
• Analyzing atmospheric vertical profile and horizontal transect data of CO2, CO, and H2O, including data quality control.
• Adapting the existing CarbonTracker-Lagrange regional inverse modeling framework to the Congo Basin domain.
• Conducting sensitivity tests of model parameter selection and atmospheric transport products.
• Comparing flux results to bottom-up estimates from terrestrial biosphere models and inventories.
• Implementing and operating models on high performance computing systems (HPCs).
• Lead and contribute to the publication of research results in the peer-reviewed literature (25%).
• Present research findings at internal meetings and national and international conferences (10%).

Requirements & Tech Stack

• Ph.D. in Atmospheric Science, Earth System Science, Data Science, Applied Mathematics, or a related field.
• Doctoral dissertations must have been successfully defended, and all manuscript revisions finalized by January 1, 2027.
• Demonstrated experience analyzing and visualizing large datasets using scientific programming languages such as MATLAB, Python, or R.
• Experience with numerical modeling, preferably on high-performance computing systems (HPCs).
• Familiarity with the carbon-cycle and land biosphere models.
• Knowledge of Bayesian inverse modeling approaches.

Qualifications

• Strong skills in analysis and visualization of large and complex observational and model datasets.
• Ability to critically interpret and diagnose model output.
• Excellent verbal and written communication skills.
• Demonstrated ability to clearly communicate results to the scientific community via peer-reviewed publications and presentations at scientific meetings.
• Ability to collaborate productively in a team and formulate independent ideas.

Appointment Details

• This is a 2-year appointment with the possibility of extension based on funding availability.
• A hybrid work modality (mix of in-person and remote) may be possible after an initial full-time in-person training period.
• The position is rostered in CIRES at the University of Colorado Boulder, located at NOAA’s David Skaggs Research Center, Boulder, CO.
• Finalists will be required to pass a federal laboratory background clearance for site access. Non-US citizens without green cards may have limited building access.
• Candidates must be eligible for full-time work and successfully complete a federal background clearance by January 1, 2027.