CIRES / NOAA Physical Sciences Laboratory Research Associate focused on Machine Learning methods for Hydrologic Predictions

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 NOAA-Physical Sciences Laboratory (PSL) mission is to conduct scientific research to observe, understand, model, predict and forecast weather, water and climate extremes and their impacts. Our vision is an informed society that uses science-based environmental intelligence to effectively anticipate and respond to threats and opportunities related to weather, water, and climate extremes. Our research goals are as follows:

• Rigorously characterize and predict weather, water, and climate extremes and their uncertainties to support NOAA's mission.
• Develop new process-understanding, observing, and modeling capabilities to predict conditions associated with too much or too little water for early warning, preparedness, resource management, and adaptation.
• Improve monitoring and prediction of weather, climate, and water conditions impacting marine resources.

• Develop and/or apply machine learning based hydrologic modeling techniques and observations to improve ensemble streamflow forecasts (30%).
• Establish data-processing workflows to obtain, manipulate, and visualize relevant observations and model output (15%).
• Work with a team of scientists to improve skill, reliability, and interpretability of hydrometeorological forecasts for targeted applications (e.g., water availability, floods, droughts, etc.) (15%).
• Conduct research to complement and enhance predictions from existing operational hydrological models. (10%).
• Prepare and present results to scientific audiences and to stakeholders via journal publications, conference presentations, participation in professional societies, and/or user-group meetings. (15%).
• Provide scientific and technical direction for experimental designs to test hypotheses and better understand limitations of machine learning methods for hydrologic simulation (10%).
• Performs other relevant duties as necessary (Not to exceed 5%).

• This position will be rostered in CIRES at the University of Colorado Boulder, but will be physically situated in the NOAA laboratory facility at the David Skaggs Research Center, 325 Broadway, Boulder, CO 80305.
• If you are selected for this position, you will be required to pass a federal laboratory background clearance for site access.
• Given project deliverables, candidates must be able to start work by March 1, 2026.
• Visa sponsorship is not offered for this position. Candidates working in the United States through a visa or a work permit or needing sponsorship now or in the future are not eligible for hire in this role.

• CIRES can offer a generous compensation package.
• The annual hiring salary range for this position is $72,000- $84,450. 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.
• This position does not offer relocation.
• An opportunity to work on the next-generation hydrologic forecast models and produce information on water risks and opportunities to support water resource decisions and management.
• 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.

• A PhD in Civil Engineering, Hydrology, Water Resources, or a related field.
• Experience using neural hydrology python package (a machine learning package developed for hydrologic predictions), https://github.com/neuralhydrology/neuralhydrology.
• Experience using Linux and developing structured code in Python, R, and/or shell scripting.

• Expertise in hydrometeorology, hydroclimatology, statistics, or data science.
• 2+ years post-PhD research experience
• Hands-on knowledge or familiarity with state-of-the-art machine learning methods.
• Interest in hydrometeorological forecasting.
• Knowledge of existing national or regional operational hydrological models and benchmarks.
• Familiarity with credible hydrometeorological and other relevant datasets suitable for training machine learning models.
• Ability to work and communicate effectively within a team environment and to facilitate communications across multiple teams and multiple organizational units.

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 and experience 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 scientific analysis and visualization tools.
• Proficiency with statistical and/or machine learning methods.
• Experience with forecast calibration and verification.
• Experience and/or interest in GPU computing for machine learning applications.

To apply please submit the following materials with your application:

• Resume or CV.
• Cover letter addressed to the Search Committee briefly describing your qualifications, professional goals, and specific interest in this position.
• Although not required at the time of application, please be ready to submit contact information for professional references (name, title, professional relationship, email) who may be contacted on your behalf. If you are selected as a finalist for this role, the search committee will request a letter 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.

The position will close on October 17, 2025.

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