R&D Mechanical Engineer - Computational Fluid Dynamics - Hybrid
New Mexico, USA
Listed on 2026-02-18
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Engineering
Mechanical Engineer, Systems Engineer
R&D Mechanical Engineer - Computational Fluid Dynamics - Hybrid
Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting‑edge work in a broad array of areas. Some of the main reasons we love our jobs:
- Challenging work with amazing impact that contributes to security, peace, and freedom worldwide
- Extraordinary co‑workers
- Some of the best tools, equipment, and research facilities in the world
- Career advancement and enrichment opportunities
- Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work 4 ten‑hour days each week) compressed workweeks, part‑time work, and telecommuting (a mix of onsite work and working from home)
- Generous vacation, strong medical and other benefits, competitive 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*
- World‑changing technologies. Life‑changing careers. Learn more about Sandia at: http://(Use the "Apply for this Job" box below)..gov
* These benefits vary by job classification.
What Your Job Will Be Like:We are seeking a Mechanical Engineer to build a research career in developing innovative approaches to the understanding and simulation of scientific and engineered systems, with an emphasis on computational fluid dynamics. You would join our collaborative team of researchers at the Computer Science Research Institute in Albuquerque, New Mexico, who are working to find creative solutions to algorithmic, performance, verification, discretization, modeling, and software engineering challenges to simulating scientific and engineering systems.
Onany given day, you may be called on to:
- Develop mathematical models and the numerical methods suitable for accurate simulation
- Perform implementation of algorithms for high performance computing environments
- Innovate in the use of AI/ML to accelerate scientific innovation
- Work independently, collaborate with the team, and partner with customers
- Contribute to scientific publications and presentations
- Develop research proposals to tackle challenges that you identify
The selected applicant can work a combination of onsite and offsite work. The selected applicant must live within a reasonable distance for commuting to the assigned work location when necessary.
Salary Range:$117,500 - $235,700
* Salary range is estimated, and actual salary will be determined after consideration of the selected candidate’s experience and qualifications, and application of any approved geographic salary differential.
Qualifications We Require:- A Bachelor’s degree in a relevant discipline and five (5) years of directly relevant experience, or an equivalent combination of directly relevant education and engineering or scientific experience that demonstrates the knowledge, skills, and ability to perform independent research and development.
Desired qualifications for a R&D Mechanical Engineer position at Sandia are:
- Graduate degree in Mechanical Engineering or a highly related field where an independent research project was a graduation requirement (e.g., independent project, thesis, or dissertation).
- Experience with mechanical engineering and product realization in the NNSA complex.
- Strong verbal and written communication skills, ability to work effectively in multidisciplinary teams, and a passion to improve and expand technical skills.
- PhD in engineering, science, or mathematics.
- Strong foundations in applied mathematics and numerical modeling, in particular, in computational fluid dynamics.
- A track record of scientific achievement through publications and presentations.
- Experience developing models and numerical methods for the accurate simulation of physical systems with fluid flows.
- Ability to find creative solutions to models and algorithm challenges.
- Experience in using or developing Machine Learning for advancing predictability of science and engineering simulations.
- Interest or experience in working on applications involving fluid flows, such as systems with suspensions, non‑Newtonian flows, geophysical flows, or…
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