CPAESS Computational Scientist V

University Corporation for Atmospheric Research (UCAR)•Boulder, CO

1d•$128,520 - $167,180•Hybrid

About The Position

UCAR is excited to announce the job opening for the Computational Scientist V role with the Cooperative Programs for the Advancement of Earth System Science (CPAESS) working with NOAA's Office of Modeling and Development (OMD). This position will focus on enhancing coupled ocean and sea ice JEDI-based data assimilation system for the Global Forecasting System (GFS) by integrating critical marine observations. This may include transition from retrieved products to direct assimilation of Level 1b radiances for sea-surface-sensitive channels to improve atmosphere-ocean balance and sea surface temperature conditions, and integrating sea ice freeboard observations to address model biases and significantly improve sea-ice forecast skill. CPAESS serves the Earth System Science community in three distinct areas of service. We partner with federal agencies and businesses to hire critical scientific staff enabling a more robust workforce. Through our scientific programs we seek to edify new research with our postdoctoral programs, our visiting scientist and internship programs, along with our interagency support programs. We also help build the Earth system science community by convening and managing summer schools and institutes, conferences, and advisory committees.

Requirements

Typically requires a minimum of a Bachelors of Science degree and 15 years related experience, or a Master’s degree and 11 years of experience, or a PhD in a scientific discipline and 7 years related experience; or an equivalent combination of education and experience.
Has expert knowledge of numerical methods, parallel computing, and high-performance computing architectures.
Possesses deep understanding of scalable software architectures and parallel computing frameworks for atmospheric process simulation.
Has extensive expertise in proposal development, technical documentation, and computational science project management.
Is proficient in developing and optimizing complex computational algorithms for large-scale environmental simulation applications.
Demonstrates analyzing and validating large-scale simulation results using advanced statistical and visualization techniques.
Is skilled in translating complex scientific results into clear visualizations and presentations for diverse stakeholder audiences.
Is a skilled mentor and team builder, capable of supporting technical development, inclusive collaboration, and cross-project alignment.
Is skilled in leadership, mentoring, and developing teams, with a focus on fostering collaborative and high-performing environments.
Is capable of leading multidisciplinary research teams while fostering collaboration between computational experts and domain scientists.
Is able to mentor less experienced scientists and shape technical direction across multiple computational science projects.
Is capable of leading and/or making significant contributions to proposal development, technical documentation, and computational science project management.
Has proven capability in delivering publications, presentations, or externally recognized outputs that reflect meaningful contributions to the field.
Is recognized as an emerging leader in computational science communities through service, collaborative influence, or participation in national initiatives.

Nice To Haves

Significant experience with atmospheric or oceanic numerical modeling.
Advanced knowledge of data assimilation methods, especially coupled data assimilation.
Proficiency with JEDI or a similar data assimilation framework.
Excellent scientific communication skills for documenting research findings and coordinating with partners.
Advanced programming skills for scientific model development and data analysis.

Responsibilities

Leading, designing, and executing complex computational research initiatives focused on Earth system science, ensuring alignment with program objectives.
Developing innovative numerical methods and computational algorithms to solve difficult scientific and engineering problems.
Directing teams in implementing and optimizing scientific software for high-performance computing environments.
Designing scalable computational frameworks that advance understanding of atmospheric and environmental processes.
Analyzing large-scale simulation results and assimilating data to validate models and extract insights for Earth system science.
Engaging with senior leadership and sponsors to shape scientific strategies, align goals with broader priorities, and guide proposal development and program planning.
Supporting the professional growth of less experienced computational scientists, mentoring, and fostering collaboration and team performance. Enabling collaboration between computational experts and other scientists.
Contributing actively to, leading, and/or co-leading papers, reports, technical documentation, data sets and findings, and proposals that advance computational science capabilities within programs, as appropriate.
Disseminating significant outcomes through peer-reviewed publications, technical tools, invited talks, stakeholder briefings, and thought leadership that influence computational science and practice.
Implementing advanced visualization techniques to communicate complex scientific results to diverse stakeholder groups.
Representing the organization in external engagements, participating in advisory roles, national panels, or collaborative initiatives with emerging influence at strategic levels.
Leading development of complex products and/or tools for projects and programs.
Conducting rigorous validation of the global data assimilation system through an iterative process. This includes analyzing model output, and evaluating the impact of assimilation techniques on model biases to drive system improvements.
Developing and configuring the JEDI system for coupled data assimilation with GFS. This involves an iterative cycle of adding new observations to the data assimilation system (e.g., direct radiance assimilation for sea surface temperature, sea ice freeboard) and refining the system based on ongoing performance feedback.
Documenting research findings and coordinating with stakeholders at NWS/OMD and partner agencies to ensure the new capabilities are ready for operational integration into the GFS system.