Job Description Summary:

NSF NCAR's CGD Laboratory is excited to announce the job opening for a Project Scientist I position. This position studies the impact of a machine-learned ocean parameterization in coupled simulations with the Community Earth System Model (CESM) and in particular its impact on the Madden-Julian Oscillation (MJO), El Nino Southern Oscillation (ENSO) and their interactions.
The scheme aims at a better representation of the vertical mixing in the ocean surface boundary layer and uses neural networks trained on data generated using a second moment closure for turbulent mixing

The work is comprised of (1) conducting coupled simulations with and without the mixing scheme (2) quantification of the impact of the machine-learned ocean parameterization on climate mean and variability, (3) investigation of the impact of the scheme on MJO, ENSO and their interactions.

This work is part of a larger international effort to use multiscale machine learning to improve coupled Earth System Models. As such, the Project Scientist will interact with a large number of Junior Researchers and PIs from multiple institutions involved in the project who are investigating different aspects of the coupled Earth System.

Position Details:

Visa Sponsored Job:

No

Relocation Assistance Eligible:

No

Job Location:

Boulder, Colorado

Position Type & Term:

Full time, Term - 6 months or more (Fixed Term)

Compensation Range:

Salary Range - $96,266 to $120,331*

*Final salary and rates are based on education, experience, skills relevant to the role.*

Application Notes

Application Deadline:

• This position will be posted until 11:59 pm MT on Tuesday, October 14, 2025.

Required application materials: (preferably in PDF Format)

• Resume
• Cover Letter - Please address how your skills and experience meet the needs of this position (for more information, please refer to the Key Responsibilities and Knowledge, Skills, and Abilities sections of this job posting).

Background Checks: Conducted for candidates selected for hire. Learn more.
Work Location: Regardless of flexible work arrangements, UCAR requires ALL positions to be
performed within the U.S., excluding U.S. Territories.

What You Will Do

Here is a brief summary of what one would expect to be generally responsible for in this role.

Under general guidance, conducts independent and collaborative research to accomplish the goals of the project:

• Designs and executes coupled experiments with CESM in an HPC environment.

• Conducts analyses of coupled simulations using existing and novel diagnostics. Due to the large volume of data this necessitates expertise in geospatial multi-dimensional HPC analysis tools and methods (i.e., python, xarray).

• When necessary, re-trains modern ML algorithms to represent vertical ocean mixing. This necessitates expertise in modern machine learning libraries and data loaders (e.g., pytorch, tensorflow, and data pipelines).

• Interacts with the project collaborators and partners regularly for coordinated / joint analysis and experimentation. Takes the lead and participates in writing scientific journal articles. Presents results at relevant meetings.

Who We'd Love To Join Our Team

Successful candidates will ensure their application materials speak to the following criteria:
Education and Experience:

Required:

Ph.D. in a relevant science; or an equivalent combination of education and experience.

Desired, but not required:

Research experience in a relevant field, with contributions to peer-reviewed journals.

Knowledge, Skills, and Abilities

Required:

• Comprehensive understanding, through published or academic work, of modeling complex, geophysical processes.

• Demonstrated understanding of atmospheric and climate dynamics.

• Knowledge of coupled climate processes including the Madden-Julian-Oscillation and ENSO.

• Demonstrated knowledge of statistical analysis and graphical presentation, in particular Python.

• Skilled in machine learning techniques.

• Excellent oral and written communication skills, with an emphasis on technical communication.

• Ability to