Job Description

The Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University (CSU) seeks to fill a full-time research associate position designed to conduct collaborative research and development with the National Oceanic and Atmospheric Administration (NOAA) located at the Global Systems Laboratory (GSL) in Boulder, CO. The individual in this position will work in the NOAA/OAR/GSL Earth Prediction Advancement Division (EPAD) Physics Branch.

Position Summary:

The individual in this position will lead the design and evaluation of output from real-time and retrospective, hypothesis-driven numerical weather and Earth system prediction model experiments. The outcomes of these experiments will be used to inform developments necessary to improve the forecast skill and physical fidelity of the Model for Prediction Across Scales (MPAS)-based numerical weather and Earth system prediction models developed by GSL, including regional forecast systems such as NOAA's Rapid Refresh Forecast System and future global forecast systems. The individual in this position will work closely with model developers on designing appropriate experiments, interpreting results, and translating results into scientific feedback to inform model development priorities. This position will report to the Ensemble Prediction Scientist.

Full Consideration Date: Thursday, September 24, 2026, 11:59pm (MT).

Essential Job Duties:

• In collaboration with model developers, designs, conducts, and evaluates hypothesis-driven experiments to quantify forecast errors in regional and global, deterministic and ensemble, physics-based and data-driven weather forecast systems and/or test and evaluate improvements proposed to reduce those errors.
• Contributes to leading the planning, maintenance, and execution of real-time and retrospective regional and global deterministic and ensemble forecast systems.
• Provides scientific feedback to inform current and future development activities.
• Serves as a subject-matter expert on routine and field-campaign observations from in situ and remotely sensed platforms to inform model development and verification.
• Contributes to formulating, executing, and tracking priorities for physics and model development for regional and global deterministic and ensemble forecast systems.
• Prepares briefing materials and presentations for branch management, internal meetings, conferences, and workshops, and regularly publishes scientific content.

Conditions of Employment:

• While an onsite presence at GSL in Boulder, CO, is preferred, remote work options will be considered. If onsite, if project circumstances allow and with satisfactory performance, up to 2 days per week of telework may be allowed.
• This full-time position requires a National Agency Check with Inquiries (NACI), tier 1 federal background check and a NOAA Common Access Card (CAC) ID badge for systems access. Therefore, only US citizens and lawful permanent residents with a physical USCIS "Green Card" are eligible.

Supervision:

• The individual in this position may eventually supervise up to two employees, as the project expands and funding is maintained.

Required Qualifications:

NOTE: In the body of your resume, please specifically address all required qualifications when describing your work experience. A resume that fails to specifically address the qualifications of this position may not be further considered by the search committee.

Education requirements:

• A Ph.D. in Atmospheric Science or related field; or
• A M.S. in Atmospheric Science or related field and

• at least two years of relevant post-M.S. experience; or
• A B.S. in Atmospheric Science or related field and
• at least five years of relevant post-B.S. experience

Other Requirements:

• At least two years of experience in numerical weather prediction testing, evaluation, and verification, including planning, coordinating, managing, and executing numerical weather prediction model experiments.
• At least two years of experience in Fortran and/or C++, Python, high-performance computing, and Linux computing environments.
• Experience communicating scientific results, such as through conference presentations, seminars, technical reports, and/or publications.

Preferred Qualifications:

NOTE: In the body of your resume, please specifically address all applicable preferred qualifications when describing your work experience. A resume that fails to specifically address the qualifications of this position may not be further considered after review by the search committee.

• Experience running and evaluating the output from numerical weather prediction models to test scientific hypotheses.
• Knowledge of state-of-the-art regional and/or global numerical weather prediction models.
• Knowledge of deterministic and/or ensemble forecast system verification techniques.
• Knowledge of ensemble forecast system design and verification.
• Knowledge of the availability and strengths/weaknesses of observations from in situ and/or remotely sensed platforms as it relates to numerical weather prediction model development and evaluation.

Application Instructions:

Applications must be submitted via online portal. We will not accept materials sent via email or other mode. NOTE: In the body of your resume, please specifically address all required qualifications and applicable preferred qualifications when describing your work experience. A resume that fails to address the qualifications of this position may not be further considered after review by the search committee. Likewise, an online application with a generic cover letter or missing a cover letter may not be further considered after review by the search committee. References will be requested for finalists and will not be contacted without prior notification of candidates. The full consideration date is Thursday, September 24, 2026, 11:59pm (MT).

Salary Range
$90,000 - $105,000 commensurate with experience and qualifications.

Required Application Documents

To apply, please upload the following applicant documents. Ensure your materials fully address the required and preferred job qualifications of the position. Please note, applicants may redact information from their application materials that identifies their age, date of birth, or dates of attendance at or graduation from an educational institution.
Cover Letter, Resume/CV
Employee Benefits

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