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Aktif Ofis Ümraniye Yayınlandı · 21.07.2026 LinkedIn Jobs Türkiye

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

National Laboratory of the Rockies

Posting Title Postdoctoral Researcher • Physics-Based Engineering Modeling and Validation for Drone Swarm Applications Location CO • Boulder Position Type Postdoc (Fixed Term) Hours Per Week 40 Working at NLR 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. Job Description 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. Basic Qualifications Must be a recent PhD graduate within the last three years. Must meet educational requirements prior to employment start date. Additional Required Qualifications 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 to quickly learn) Python and/or MATLAB, Fortran and/or C++, and high-performance computing environments. Preferred Qualifications Experience with wind turbine modeling tools used, e.g., FAST/OpenFAST, Bladed, and/or HAWC2. Experience with wind-farm modeling tools, e.g., FLORIS, FAST.Farm, and/or DWM for wind farms. Comfort with standard software workflows on GitHub. Familiarity with uncertainty quantification and machine-learning principles. Knowledge of fidelity-first computational fluid dynamics (CFD) modeling. Experience with processing measurement data. Job Application Submission Window The anticipated closing window for application submission is up to 30 days and may be extended as needed. Annual Salary Range (based on full-time 40 hours per week) Job Profile: Postdoctoral Researcher / Annual Salary Range: $76,600 - $126,400 NLR takes into consideration a candidate’s education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions. Benefits Summary Benefits include medical, dental, and vision insurance; short-term disability insurance ; pension benefits ; 403(b) Employee Savings Plan with employer match ; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; and paid holidays. NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Based on eligibility rules Badging Requirement NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Drug Free Workplace NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug. If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn. Submission Guidelines Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application. Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Reasonable Accommodations E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish. E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.
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