Computational Atmospheric Scientist

Posting Title Computational Atmospheric Scientist.

Location CO - Boulder.

Position Type Limited Term (Fixed Term).Hours Per Week
40.Working at NLRNLR’s 305-acre Flatirons Campus is the nation’s premier wind energy, water power, and grid integration research facility. Nestled south of Boulder, Colorado, and north of NLR’s main South Table Mountain campus, Flatirons Campus sits adjacent to the Rocky Flats National Wildlife Refuge and countless acres of open space and parks with stunning views of the Flatirons rock formations.

Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions.

Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.

At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.

Job Description NLR’s 305-acre Flatirons Campus is the nation’s premier wind energy, water power, hybrid systems, and grid integration research facility. The National Wind Technology Center at the NLR Flatiron’s Campus is seeking a qualified candidate with a strong background in atmospheric turbulence and high-fidelity computational fluid dynamics skills that can be deftly applied to wind energy, ocean energy, solar energy, and hybrid systems.

We offer a unique collaborative environment with world-renowned scientists in the area of renewable energy and atmospheric science.

The successful candidate is expected to conduct research on energy resources in the atmosphere, extreme weather events and their impact on infrastructure, and other related topics related to wind, water, solar, and hybrid energy systems. Candidates should demonstrate a broad understanding and wide application of atmospheric, fluid dynamic, and scientific computing principles, theories, and concepts. A general knowledge of wind and solar energy related disciplines and applications is an advantage.

The Researcher will primarily use lab-developed software including ERF (an energy-focused implementation of WRF with modern computing) and kynema (formerly Exa Wind). Simulations are likely to span regional-scale weather (mesoscale), the project-scale atmospheric-boundary-layer flow (microscale), infrastructure asset scale, and the coupling between all of them. Additional tools may include AI/ML surrogates and forecasting models, WRF, and data assimilation of remote measurements.

The successful candidate will be able to execute research tasks independently but is also expected to collaborate well in larger project teams and follow the guidance of senior staff. The researcher will work collaboratively with the US Department of Energy’s Office of Critical Materials and Energy Innovation, other national laboratories, academia, industry partners, and the international community to solve challenging science and engineering problems in energy.

The position requires excellent interpersonal and communication skills and the desire and ability to lead peer-reviewed journal publications from start to finish.

Any code development in research projects will be done in the open-source domain with adherence to best practices in modern software engineering. Simulations will be performed on some of the world’s fastest GPU-accelerated supercomputers operated by the U.S. Department of Energy. Familiarity with high-performance computing environments to solve pressing science and engineering challenges is a plus..Basic Qualifications Relevant PhD . Or, relevant Master's…