Job Details

CIRES / NOAA Physical Sciences Laboratory: Earth System AI Scientist

Position Number: 6991942
Location: Boulder, CO
Position Type: Science - Other Science

CIRES / NOAA Physical Sciences Laboratory: Earth System AI Scientist

Requisition Number: 70475
Location: Boulder Colorado
Employment Type: Research Faculty
Schedule: Full Time
Posting Close Date: 24-Mar-2026
Date Posted:

Job Summary

The Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado at Boulder (CU Boulder) within the NOAA Physical Sciences Laboratory is seeking a research scientist with experience in Earth systems and Artificial Intelligence (AI) and Machine Learning (ML). This scientist will have the opportunity to contribute to the advancement of research in the space of AI/ML forecasting including future operational AI models at NOAA, using AI in conjunction with atmospheric and/or coupled models and data assimilation, and the enhancement of reanalysis with AI tools. This role will include work on developing, optimizing, and implementing AI models and training pipelines and evaluating results of models.

This work will contribute in part to the larger NOAA Project EAGLE (https://www.epic.noaa.gov/ai/eagle-overview/). The incumbent will work with an established team of scientists to develop and exercise AI forecasting models on a diverse combination of High-Performance Computing (HPC) and cloud platforms, conduct data management, and provide scientific evaluation of the results across Earth system components.
CU is an Equal Opportunity Employer and complies with all applicable federal, state, and local laws governing nondiscrimination in employment. We are committed to creating a workplace where all individuals are treated with respect and dignity, and we encourage individuals from all backgrounds to apply, including protected veterans and individuals with disabilities.

Who We Are

CIRES is an internationally recognized leader in innovative environmental science and research and is located at the University of Colorado Boulder. At CIRES, more than 900 environmental science professionals work to understand the dynamic Earth system, including people's relationship with the planet. CIRES has partnered with NOAA since 1967, and our areas of expertise include weather and climate, changes at Earth's poles, air quality and atmospheric chemistry, water resources, solid Earth sciences, and more. Our vision is to be instrumental in ensuring a sustainable future environment by advancing scientific and societal understanding of the Earth system.

This position will be embedded in the NOAA Physical Sciences Laboratory (https://psl.noaa.gov), whose overarching research goal is to advance the prediction of water availability and extremes. Our team is located under the Modeling and Data Assimilation division (https://psl.noaa.gov/research/divisions/mda/) and is focused on improving modeling, data assimilation, and reanalysis using AI and ML tools including the work being done with Project EAGLE (https://www.epic.noaa.gov/ai/eagle-overview/).

What Your Key Responsibilities Will Be

Develops and implements AI model development and training pipelines (50%)
Optimizes, advances, and evaluates AI data and training pipelines (25%)
Evaluates results for Earth system components (20%)
Works with team members to advance AI/ML knowledge within the lab (5%)

What You Should Know

This position will be rostered in CIRES at the University of Colorado Boulder but will be physically situated in the David Skaggs Research Center, 325 Broadway, Boulder, CO 80305.
If you are the finalist, you will be required to pass a background check. Non-US citizens without green cards will have limited building access and require a federal escort in the building.
Some domestic or international travel is expected to attend conferences, as relevant.
Given project deliverables, candidates must be able to start work by August 1st, 2026.

What We Can Offer

CIRES offers a generous compensation package.
The annual hiring salary range for this position is $74,933 - $135,896. Salary is commensurate with education and experience and determined based on our CIRES internal career-track classification.
This position can accommodate a hybrid work modality.
Some relocation funds are available to help offset expenses, following CIRES and the University of Colorado's relocation processes and procedures.
The University of Colorado Boulder offers a robust training curriculum, opportunities for professional development and a Mentorship Program.
Boulder is a vibrant community with access to mountain parks, dog parks, miles of trails, rivers, lakes, cafes, restaurants, boutiques, theaters, museums, and sports venues.
As an employee at CU Boulder, you will have free access to the regional public transit system, an outstanding network of buses and light rail systems that service Boulder and connect to Denver, the Denver airport, and surrounding communities.

Benefits

At the University of Colorado Boulder, we are committed to supporting the holistic health and well-being of our employees. Our comprehensive benefits package includes medical, dental, and retirement plans; generous paid time off; tuition assistance for you and your dependents; and an ECO Pass for local transit. As one of Boulder County's largest employers, CU Boulder offers an inspiring academic community and access to world-class outdoor recreation. Explore additional perks and programs through the CU Advantage program.

Be Statements

Be innovative. Be successful. Be Boulder.

What We Require

PhD in Earth Sciences, Meteorology, Math, or Computer Science or related field. Candidates must have successfully defended and submitted their doctoral dissertation before starting work with CIRES.
Experience with developing and/or running AI / ML pipelines and/or models.
Experience with writing software using scripting language such as Python, MATLAB, R, NCL, or Shell.
Knowledge of Earth System Science.

What You Will Need

For all applicants:

Ability to work and communicate effectively within a team environment and to facilitate communications across multiple teams and multiple organizational units.
Ability to question experimental results to ensure they are consistent with intended design of the experiment.
Ability to develop and implement solutions to problems within existing codebases.
Basic knowledge of Earth system models or weather forecasting systems.

For advanced level scientists:

Ability to guide team members in developing and implementing AI/ML pipelines.
Ability to lead scientific experiments and implement resulting solutions.

Special Instructions

To apply, please submit the following materials:

Resume or CV.
Cover letter addressed to the Search Committee briefly describing your qualifications, professional goals, and how this position aligns with your research interests.
Although not needed at the time of application, please be ready to submit contact information for 5 professional references, including at least 2 managers or professors. If you are identified as a finalist for this position, you will be asked to invite your references to complete a Crosschq questionnaire on your behalf. Crosschq is an online reference check solution. All information is kept confidential and shared only with the members of the search committee.

If you are selected as the finalist, your degree will be verified by the CU Boulder Campus Human Resources department using an approved online vendor. If your degree was obtained outside of the United States, please submit a translated version as an optional attachment.

This position will close March 24, 2025.

Note: Application materials will not be accepted via email. For consideration, applications must be submitted through CU Boulder Jobs.

In compliance with the Colorado Job Application Fairness Act, in any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

To apply, visit https://jobs.colorado.edu/jobs/JobDetail/CIRES-NOAA-Physical-Sciences-Laboratory-Earth-System-AI-Scientist/70475