Publisher
source

Chitrarth Prasad

2 months ago

Postdoc in Data-Driven Discovery for Vortex-Dominated Flows Oklahoma State University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Postdoctoral research position; funding details, stipend, and duration are not specified in the post.

Country flag

Country

United States

University

Oklahoma State University

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Keywords

Computer Science
Machine Learning
Aerodynamics
Mechanical Engineering
Aerospace Engineering
Mathematics
Physics

About this position

Postdoctoral opening in vortex-dominated flows at Oklahoma State University with Assistant Professor Chitrarth Prasad. The project spans computational fluid dynamics, experimental fluid dynamics, and data-driven discovery for unsteady aerodynamic and vortex-dominated flows.

The postdoc will develop and apply machine learning, reduced-order modeling, and other data-discovery methods to challenging flow problems. This is a strong fit for candidates with backgrounds in mechanical engineering, aerospace engineering, applied mathematics, or related areas with experience in fluid mechanics and data-driven methods.

Eligibility highlights: applicants should have relevant research experience in CFD and/or experimental fluid dynamics, and the post explicitly asks for prior machine-learning work, especially if it has been applied to fluid dynamics. Candidates already in the U.S. and able to start in late August or early September 2026 are preferred.

How to apply: email [email protected] with a CV and a brief description of your relevant research experience. Be sure to include specific examples of prior machine-learning work.

No formal deadline is listed in the post, but the anticipated start date is late August or early September 2026, so interested candidates should apply promptly.

Funding details

Postdoctoral research position; funding details, stipend, and duration are not specified in the post.

What's required

Applicants should have relevant research experience in computational and/or experimental fluid dynamics. Prior machine-learning experience is specifically requested, especially applications involving fluid dynamics. Candidates already in the United States and available to start in late August or early September 2026 are preferred.

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Professors

Assistant Professor

University Name
Country flag

United States

Research Interests

Aerodynamics

Fluid Mechanics

Supersonic Flow

Jet Physics

Noise Control