Postdoctoral Fellow I

Final salary and rates are based on education, experience, and skills relevant to the role.

Term - 6 months or more (Fixed Term)

Yes

Yes

82,650.00 USD - 82,650.00 USD

This position will be posted until 11:59:59 pm MDT on Sunday, August 30, 2026.

We seek a motivated postdoctoral fellow to contribute to cutting‑edge research in coupled atmosphere‑aerosol‑land data assimilation and forecasting within NSF NCAR’s Mesoscale and Microscale Meteorology (MMM) Laboratory. The fellow will help advance satellite data assimilation capabilities and conduct cycling analysis and forecast experiments using a variety of real‑world observations.

The primary research platform will be our next‑generation, online‑coupled community analysis and forecasting system, based on the Model for Prediction Across Scales and interfaced with the Joint Effort for Data Assimilation Integration. The fellow will also be encouraged to explore various algorithms, including, but not limited to, artificial intelligence and machine‑learning approaches, through targeted case studies.

Depending on project needs and the fellow’s expertise and interests, the work may involve collecting and processing observational and model datasets; advancing data assimilation algorithms and observation operators; and developing postprocessing tools, cycling infrastructure, and workflow scripts. The fellow will also have opportunities to contribute to the implementation of coupling capabilities in the system and innovative approaches to satellite data assimilation.

The new hire will work both independently and collaboratively in an interdisciplinary research environment, apply sound scientific interpretation to experimental results, advance the use of satellite observations in atmospheric composition and/or weather forecasting, and publish findings in peer‑reviewed journals.

Conducted for candidates selected for hire. Learn more.

Regardless of flexible work arrangements, UCAR requires ALL positions to be performed within the U.S., excluding U.S. Territories.

Conduct independent and collaborative research in satellite data assimilation and coupled analysis and forecasting. Design and perform cycling analysis and forecast experiments using the MPAS‑GOCART2G‑JEDI system to evaluate the impact of remote sensing observations. This work may include developing or improving capabilities for data collection, processing, postprocessing, visualization, and end‑to‑end cycling workflows.

Explore innovative data processing or data assimilation methods, including AI/ML approaches, through targeted case studies. Analyze and scientifically interpret experimental results; evaluate the impacts of assimilated observations and methodological developments on atmospheric analyses and forecasts; diagnose system performance; identify limitations; and recommend improvements based on quantitative verification and scientific understanding.

Communicate research findings and support project activities. Prepare research results for presentation at scientific conferences and publication in peer‑reviewed journals. Assist with the preparation of scientific proposals, project progress reports, and related documentation, as needed.

Successful candidates will ensure their application materials speak to the following criteria:

• Ph.D. degree within the last 5 years or expected within the next 6 months in atmospheric science, computer science, statistics, or a related area.
• Makes decisions about research tools and methods for investigating satellite data assimilation algorithms. Designs and implements approaches to data collection, experiment execution, data analysis, and scientific interpretation, with guidance from the supervisor and input from other members of the project team. Develops and implements research plans aligned with project priorities. Creatively and efficiently solves scientific problems as part of a team.
  
  Communicates with team members…