Postdoctoral Researcher – Physics-Based Engineering Modeling and Validation for Drone Swarm App

Posting Title

Postdoctoral Researcher – Physics-Based Engineering Modeling and Validation for Drone Swarm Applications

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CO – Boulder

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Postdoc (Fixed Term)

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40

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NLR’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.

The National Wind Technology Center at the NLR Flatiron’s Campus is seeking a qualified candidate to help execute projects related to physics‑based engineering modeling and validation for drone swarm applications. The researcher will adopt physics‑based engineering tools previously developed for wind turbine and wind‑farm tools applications (e.g., OpenFAST and FAST.Farm) to drone swarm applications, including individual drone aero‑servo‑elastics and drone‑wake/downwash interaction.

The engineer will identify and support improvements to the engineering tools through theory development and software implementation. They will systematically verify and validate (V&V) the tools through comparisons to fidelity‑first modeling results (e.g., Kynema) and measurement data to quantitatively understand their applicability, accuracy, and limitations. They will also collaborate with other researchers focused on drone fidelity‑first modeling, drone swarm control, and drone swarm applications.

The researcher will be able to move fluidly between theory development, software implementation, model V&V, and applications.

The researcher will work with a wide variety of customers including the U.S. Department of Energy Integrated Energy Systems Office. They may also work collaboratively with other national laboratories, industry and academic partners, and the international community to execute projects. The researcher is expected to demonstrate a broad understanding and wide application of engineering principles, theories, and concepts as well as general knowledge of drone‑related disciplines, applications and challenges.

Candidates with aerospace or mechanical engineering backgrounds with some knowledge of wind engineering and/or drone applications are encouraged to apply.

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Must be a recent PhD graduate within the last three years.

*** Must meet educational requirements prior to employment start date.**

The successful candidate will have excellent writing, interpersonal, and communication skills. The candidate will be expected to publish research results in technical journals/conference proceedings and present work at conferences, symposia, and review meetings. They may also be expected to support the development of new work proposals, preparations, and reviews.

In addition, the candidate is expected to have:

• Experience with physics-based drone modeling principles, including aerodynamics, structural dynamics, and/or controls.
• Experience with programming languages, including familiarity with (or the ability…