Postdoctoral Researcher - Physics-Based Engineering Modeling and Validation for Drone Swarm Applications
About The Position
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.
Requirements
- Recent PhD graduate within the last three years.
- Meet educational requirements prior to employment start date.
- Excellent writing, interpersonal, and communication skills.
- 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.
Nice To Haves
- 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.
Responsibilities
- Adopt physics-based engineering tools for drone swarm applications, including individual drone aero-servo-elastics and drone-wake/downwash interaction.
- Identify and support improvements to engineering tools through theory development and software implementation.
- Systematically verify and validate (V&V) tools through comparisons to fidelity-first modeling results and measurement data.
- Collaborate with other researchers focused on drone fidelity-first modeling, drone swarm control, and drone swarm applications.
- Move fluidly between theory development, software implementation, model V&V, and applications.
- Work with a wide variety of customers including the U.S. Department of Energy Integrated Energy Systems Office.
- Collaborate with other national laboratories, industry and academic partners, and the international community to execute projects.
- Publish research results in technical journals/conference proceedings.
- Present work at conferences, symposia, and review meetings.
- Support the development of new work proposals, preparations, and reviews.
Benefits
- 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
- Paid holidays
- Performance-, merit-, and achievement- based awards that include a monetary component (eligibility not guaranteed)
- Relocation expense reimbursement (eligibility not guaranteed)
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
