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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.

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Country

United States

University

Virginia Tech

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Keywords

Computer Science
Mechanical Engineering
Aerospace Engineering
High Performance Computing
Supersonic Flow
Particle Transport
ML

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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

University Name
Country flag

United States

Research Interests

Aerospace Engineering

High Performance Computing

Mechanical Engineering

Supersonic Flow

Computer Science

Prof. at Virginia Tech

University Name
Country flag

United States

Research Interests

Aerospace Engineering

Mechanical Engineering

High Performance Computing

Computer Science

Particle Transport