Description
Serve as a Research AST, Computational Scientist in the Computational
Aerosciences Branch of the Research Directorate, performing research and
development in
computational science for aerospace vehicles with applications in all speed
regimes, from subsonic to hypersonic flight. The focus of the research is to
develop new
physics-based prediction methods and extensions of existing methods for the
analysis and design of complex three-dimensional configurations, including
verification, validation and the use of massively parallel high-performance
computing architectures.
Duties
• Develop, apply and validate new computational fluid dynamics
techniques/algorithms tailored to advanced and/or emerging computer hardware
technology for
computational aerosciences applications (CFD, error estimation, grid adaptation,
multi-physics applications, etc.)
• Develop advanced techniques and models for the prediction and control of
turbulent flows, with an emphasis on the high Reynolds number flows encountered
on full-
scale aircraft configurations.
• Report findings at technical conferences and in the scientific literature.
• Serves as a technical expert and interfaces with other researchers in
industry, universities, NASA, and other government agencies
• Conducts research in problem areas that are highly complex and of considerable
scope. Problems are often difficult to define, require novel approaches and
sophisticated research techniques
• Duties may include monitoring and evaluating research contracts and grants to
accomplish collaborative research with external organizations.
Requirements:
• MS in engineering, applied mathematics, computer science, physics, or
equivalent, with strong background in (1) developing, applying and validating
computational
fluid dynamics algorithms on high-performance computer architectures for
aeroscience applications, (2) planning, conducting and reporting on professional
research
topics related to physics-based prediction methods, and (3) writing, reporting,
and presenting results to include publications.
• A desire to quickly learn and apply new paradigms relevant to current and
emerging computational methods, and an eagerness to work in a team environment.
• Ability to successfully complete a background investigation required to obtain
a NASA badge.
• US citizenship or permanent resident status is a bona fide requirement.
Desired Skills:
• PhD preferred
• Knowledge of fluid mechanics, numerical methods, and/or physical modeling
techniques.
Company Description
About NASA and the Computational AeroSciences Branch – The advertised position
will reside in the Computational AeroSciences Branch (CASB) in the Research and
Technology Directorate at NASA Langley Research Center (Langley Research Center
| NASA) in Hampton, Virginia. The branch mission is to develop and apply
aerodynamic
and acoustic simulations methods for aerospace vehicles with applications in all
speed regimes, from subsonic to hypersonic flight. The branch works to improve
the
fundamental understanding of physics associated with the fluid mechanics (e.g.,
transition and turbulence) and noise generation for complex aerospace systems.
Research is carried out to develop new physics-based prediction methods and
extensions of existing methods for the analysis and design of complex three-
dimensional
configurations, including verification, validation and the use of massively
parallel high-performance computing architectures. Of particular interest is
research for
development of advanced techniques and models for the prediction and control of
turbulent flows, with an emphasis on the high Reynolds number flows encountered
on
full-scale aircraft configurations. Objectives of the research conducted in the
branch include: to advance the state-of-the art of CFD for efficiency, accuracy
and
robustness; flow control; efficient design of aerospace vehicles; methods for
airframe noise prediction and control of noise sources. Research is accomplished
through the formulation, conduct, analysis, correlation, documentation, and
dissemination of results from various research studies.
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