Chris Roy
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Postdoctoral Associate in Aerospace Engineering: Machine Learning for Hypersonic CFD and Experimental Model Validation Virginia Tech in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Funded research position with salary listed as 63,480-65,000 USD per year, commensurate with experience. The projects are funded by the US Navy (ONR and NAWCAD) and supported by AFRL and industry sponsors.
Country
United States
University
Virginia Tech
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About this position
The Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech is seeking a postdoctoral associate for a two-part research program at the university’s main campus in Blacksburg, Virginia.
One half of the appointment focuses on hypersonic aerodynamics and computational fluid dynamics. Working with Prof. Chris Roy and collaborators at Spectral Sciences, Inc., the researcher will apply machine learning tools to improve turbulence modeling for CFD prediction of hypersonic flows. The project centers on Favre-Averaged Navier-Stokes turbulence models and physics-constrained machine learning methods aimed at improving predictions of surface heating, skin friction, and flow separation.
The other half of the role is linked to experimental and model-validation work with Prof. Todd Lowe and the Virginia Tech Advanced Propulsion and Power Laboratory. This component supports ongoing and future CFD model validation and development experiments, including work on engine inlet distortion and engine particle transport with government and industry partners.
The position sits within a research environment that combines aerospace engineering theory, simulation, and laboratory experimentation. The advert also notes opportunities for teaching and service-related activities, and it emphasizes the need for strong communication and teamwork in a collaborative setting.
Funding details
Funded research position with salary listed as 63,480-65,000 USD per year, commensurate with experience. The projects are funded by the US Navy (ONR and NAWCAD) and supported by AFRL and industry sponsors.
What's required
Ph.D. in Aerospace Engineering, Mechanical Engineering, or a related discipline; the doctorate must have been awarded no more than four years before the effective date of appointment, with at least one year of remaining eligibility. Applicants must have experience conducting research in computational fluid dynamics, experience with Reynolds- and/or Favre-averaged Navier-Stokes turbulence models, experience programming in modern Fortran, C, C++, or Python, and US citizenship or US permanent residency due to sensitivity of the work. Preferred qualifications include experience with machine learning techniques, experimental fluid dynamics techniques, high-speed compressible flows, and high-performance computing. Strong communication skills and the ability to work effectively in a team are also desired.
How to apply
Apply through the Virginia Tech careers portal using the provided application link. Prepare materials demonstrating your CFD, turbulence modeling, programming, and any machine learning or experimental fluid dynamics experience. Be ready for a criminal conviction check if selected.
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Professors
Prof. at Virginia Tech
United States
Research Interests
Aerospace Engineering
High Performance Computing
Mechanical Engineering
Supersonic Flow
Computer Science
Prof. at Virginia Tech
United States
Research Interests
Aerospace Engineering
Mechanical Engineering
High Performance Computing
Computer Science
Particle Transport
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.