New

CIRES/NOAA Global Systems Laboratory, Satellite Data Assimilation Scientist

University of Colorado
$72000.00-$114000.00
paid time off, tuition assistance, remote work
United States, Colorado, Boulder
Sep 24, 2026
Requisition Number: 75030 Location: Boulder, Colorado City Boulder State Colorado Employment Type: Research Faculty Schedule: Full-Time Posting Close Date: 08-Oct-2026 Date Posted: 24-Sep-2026 Close All Job Summary The Cooperative Institute for Research in Environmental Sciences (CIRES), a partnership of the University of Colorado Boulder and the National Oceanic and Atmospheric Administration, has a job opening for a Satellite Data Assimilation Scientist at the NOAA Global Systems Laboratory (GSL) located in Boulder Colorado. The Data Assimilation Branch (DAB) within GSL's Assimilation and Verification Innovation Division (AVID) develops and advances data assimilation capabilities for operational numerical weather prediction systems supporting a wide range of applications, including aviation, severe weather, renewable energy, and general weather forecasting. The Rapid Refresh Forecast System (RRFS) is NOAA's convection-allowing data assimilation and forecast system designed to provide rapidly updated, high-resolution weather forecasts over North America. In collaboration with other partners, GSL is developing and improving RRFS using the Model for Prediction Across Scales (MPAS) and the Joint Effort for Data Assimilation Integration (JEDI) framework. To support NOAA's Geostationary Extended Observations (GeoXO) program, NOAA/GSL has been evaluating the data impact of hyperspectral infrared radiance data from polar-orbiting satellites and is also expanding to evaluate the data impact from geostationary hyperspectral infrared sounder data (i.e., the recently available Meteosat Third Generation Infrared Sounder (MTG-IRS) data). CIRES/NOAA GSL seeks a Satellite Data Assimilation Scientist to join the Data Assimilation Branch and contribute to the continued development and improvement of RRFS. The scientist will develop, evaluate, and test modifications in data assimilation procedures for satellite and other observations in RRFS, with a particular focus on satellite radiance data (e.g., MTG-IRS data) and satellite retrieval products. The candidate will work collaboratively with scientists at GSL, external partners, and the broader RRFS and UFS modeling communities. 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. The Global Systems Laboratory (GSL) is one of ten NOAA Research laboratories and is located in Boulder, Colorado. GSL researchers develop the-state-of-the-art weather and air quality models, state-of-the-science decision support tools and visualization systems and use high-performance computing technology to support a Weather-Ready Nation. GSL strives to advance its workforce scientifically, technically, and professionally. What Your Key Responsibilities Will Be Development and testing of assimilation of hyperspectral sounding radiance from Meteosat Third Generation Infrared Sounder (MTG-IRS). (45%) Development and testing of assimilation of satellite retrieval products from Meteosat Third Generation Infrared Sounder (MTG-IRS) and other sounding retrieval data. (45%) Tune and optimize satellite data assimilation within the MPAS-JEDI based RRFS. (10%) A scientist assigned at the Research Scientist II level will take the following additional responsibilities: demonstration of independency and leadership. Contribute to the retrospective and real-time RRFS experiments to evaluate novel weather observations and data assimilation innovations. A scientist assigned at the Research Scientist III level will further take more responsibilities as below: May be asked to supervise employees, lead projects. Substantial and unique contributions to the atmospheric data assimilation, especially satellite data assimilation. 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, on a federal research campus. Selected finalists will be required to pass a federal background check for site access. Foreign nationals' access to the federal facility will be limited to weekdays, and with the presence of a federal escort. Due to project deliverables, the targeted start date for this position is by March 1, 2027. What We Can Offer CIRES offers a generous compensation package. The annual hiring salary range for this position is $72,000- $114,000. Salary is commensurate with education and experience and determined based on our CIRES internal career track classification. The preferred modality for this position is either in-person or hybrid, but we may accommodate a fully remote work modality at the supervisor's discretion, Some relocation funds are available to help offset expenses, following CIRES and the University of Colorado's relocation processes and procedures. CIRES and the University of Colorado Boulder offer 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. In fact, CU Boulder has been named one of Forbes' America's Best Large Employers, ranking #4 among large employers in Colorado and #28 among universities nationwide. Explore additional perks and programs through the CU Advantage program. Be Statements Be enlightened. Be unique. Be Boulder. What We Require Ph.D. in meteorology, atmospheric science, or relevant field of study. Minimum of 1 year of experience working on atmospheric data assimilation. What You Will Need Strong programming skills in at least one modern advanced programming language (e.g. Fortran or C++). Demonstrated ability to use a version control system (e.g. Git/GitHub). Demonstrated ability to work in high-performance computing environments. Demonstrated ability to work independently and as part of a team. What We Would Like You to Have Please note that while the position details both required and preferred skills and experience, we invite applicants to apply even if they do not have the preferred skills outlined in this section. If you meet the requirements and have passion for the work, you are encouraged to apply. We encourage on the job training for any additional skills or knowledge that become relevant to the position. Experience with meteorological data assimilation (JEDI, GSI, or DART, etc.). Experience with analyzing satellite observations and their impact in data assimilation systems. Experience with satellite radiance data including data assimilation work on hyperspectral radiance data (e.g., AIRS/CrIS/IASI/MTG-IRS). Expertise with radiative transfer models (e.g., CRTM/RTTOV) used with satellite radiance data. Knowledge of satellite observations, satellite retrievals and the associated error characteristics and averaging kernels. Experience with one or more of the following programming languages: Fortran, C++, Python, Linux Shell scripting languages. Experience with scientific data formats (grib2, NetCDF, BUFR). Excellent written and oral presentation skills. 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 specific interest in this position. Contact information (name, title, affiliation, email) for 3 references familiar with your professional qualifications for the position. You don't need to include letters of recommendation with your initial application. If you are identified as a finalist for this role, the search committee will request letters of recommendation at a later time. 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. Please apply by October 8, 2026 for consideration. Note: Application materials will not be accepted via email. For consideration, please apply 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.