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CIRES/NOAA Physical Sciences Laboratory, Post-Doctoral Associate in Multiyear Hydroclimate Predictability: Data-Driven Modeling

Requisition Number:



Boulder, Colorado





Employment Type:

Research Faculty



Posting Close Date:


Date Posted:


Job Summary

Understanding the predictability of the climate system greater than a year in advance is a critical challenge in supporting the management of water resources. This Post-Doctoral position will investigate data-driven methods to predict regional hydroclimate beyond year-1, with a specific focus on predictive understanding of western North America hydroclimate (temperature, precipitation, soil moisture, etc.) and its primary climatic drivers (e.g. ENSO and other oceanic variability).

The chosen candidate will develop and evaluate new data-driven models to examine seasonal climate predictability at lead times from 1-3 years. Emphasis will be on developing and improving machine learning models that predict the time evolution (that is, dynamics) of the system. The position will be part of the S2S2D (sub-seasonal to seasonal to decadal) team at PSL. The work will build on and extend the extensive contributions of the S2S2D team in using data-driven and machine learning methods applied to observational data, reanalyses, and forecast model output to study predictability and develop experimental forecast products.

While the focus of this position is on developing and evaluating improved prediction methods and a better understanding of hydroclimate predictability on these time scales, the eventual goal of the project is to provide the California Department of Water Resources (DWR) with probabilistic long-term outlooks.

The candidates should have excellent technical and communication skills and be comfortable working in a team environment. This is a two-year position with the possibility of extension to a third year based on performance and achievement of project goals and the availability of funding. The position is located in Boulder, Colorado.

The University of Colorado Boulder is committed to building a culturally diverse community of faculty, staff, and students dedicated to contributing to an inclusive campus environment. We are an Equal Opportunity employer, including 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 950 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.

At the NOAA-Physical Sciences Laboratory, our 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.

What Your Key Responsibilities Will Be

  • Conduct research on multi-year climate system forecasting and predictability with a focus on hydroclimate that is relevant to the missions of NOAA PSL, California DWR and their partners.
  • Develop and evaluate machine learning and empirical models.
  • Work collaboratively with a research team, including colleagues at NOAA, California DWR, and academic institutions.
  • Effectively share research results with colleagues, stakeholders, and the broader science community through technical documentation, sharing of data and models, peer-reviewed publications, and presentations.

What You Should Know

  • This is a two-year position with the possibility of extension to a third year based on performance, achievement of project goals and the availability of funding.
  • 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 selected for this position you will be required to pass a federal laboratory background clearance for site access. Non-US citizens without green cards may have limited building access, and require an escort in the building.
  • Normal working hours will be observed except for occasional irregular hours during data collection or conferences/workshops conducted at remote sites.

What We Can Offer

  • CIRES can offer a generous compensation package.
  • The annual hiring salary range for this position is $64,500 - $70,000. Salary is commensurate with experience and determined based on our CIRES internal career track classification.
  • Relocation funds are available for this position following CIRES and the University of Colorado’s relocation processes and procedures.
  • This position can accommodate a hybrid work modality.
  • 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. Boulder was recently ranked as one of the top places to live in the U.S. by U.S. News.
  • As an employee at CU Boulder, you receive a pass allowing free access to the regional public transit system, which is an outstanding network of buses and light rail systems that provide service within Boulder and connect to Denver, the Denver airport, and surrounding communities.


The University of Colorado offers excellent benefits, including medical, dental, retirement, paid time off, tuition benefit and ECO Pass. The University of Colorado Boulder is one of the largest employers in Boulder County and offers an inspiring higher education environment. Learn more about the University of Colorado Boulder.

Be Statements

Be effective. Be strategic. Be Boulder.

What We Require

  • Ph.D. in a physical science with expertise in meteorology, oceanography, hydrology or related discipline; or Ph.D. in applied math, data science, or related discipline.
  • A publication and presentation record that is commensurate with experience.
  • Experience with machine learning/data-driven modeling.

What You Will Need

  • Desire and ability to work in an inclusive and collaborative environment.
  • Fluency in writing and speaking English, and good oral and written communication skills, at a level appropriate for conference presentations and preparation of manuscripts for publication in peer-reviewed journals.
  • Expertise in data analysis or data-driven modeling.
  • Excellence in self-guided, motivated, and original research.
  • Ability to develop structured code in commonly used languages.

What We Would Like You to Have

We invite applicants to apply even if they do not have the preferred skills and experience outlined in this section. If you meet the minimum qualifications 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 creating, training, and evaluating machine learning/empirical methods used for time-series prediction
  • Familiarity with techniques that may be used to make climate forecasts, either empirical/machine learning or physically-based
  • Familiarity with climate model and forecast model output such as that from large ensembles
  • Experience with the use of common machine learning software packages

Special Instructions

To apply, please submit the following materials:

  1. Resume or CV
  2. Cover letter addressed to the Search Committee briefly describing your qualifications, professional goals, and specific interest in this position.
  3. List of contact information for 3 references who will be willing to write a confidential Letter of Recommendation for you if you are identified as a finalist for this position. Please include a list of their names, title, your relationship to you and current email and phone number.

If you are selected as a finalist, your degree will be verified by CU Boulder Campus HR 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 be open until June 6, 2024. Applications will be screened as they are received.

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

Posting Contact Information

Posting Contact Name: Joeseph Barsugli

Posting Contact Email: