Postdoc in DNS of Boundary-Layer Transition and Control at the University of Arizona University of Arizona in United States

PhD studentship at the University of Arizona on DNS of hypersonic boundary-layer transition . The project uses high-fidelity Direct Numerical Simulations (DNS) to study stability and laminar-turbulent transition in boundary layers at hypersonic speeds ( M = 4 to 14 ). Research topics include the physical mechanisms governing the linear and nonlinear stages of transition, breakdown to turbulence, and the investigation of promising flow-control methods using high-fidelity DNS. The position is well...

Kshiteej Deshmukh, Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of Nevada, Reno, has launched the Multiscale and Spatiotemporal Mechanics research group. The group works on computational mechanics , multiscale mechanics , materials science , and related theory-driven research questions about how macroscopic material behavior can be engineered through deliberate microstructure design. The research spans scales from quantum to continuum and consid...

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 ,...

Oklahoma State University is advertising a postdoctoral researcher position in machine learning for fluid dynamics through its Flow Physics Simulation Laboratory . The project focuses on applying ML and data-driven discovery methods to vortex-dominated flows , unsteady aerodynamics , computational fluid dynamics (CFD) , and experimental fluid dynamics . The role is a strong fit for researchers interested in combining machine learning , reduced-order modeling , and fluid mechanics. Responsibiliti...

Ahmad Peyvan is recruiting two fully funded PhD students to join his research group in the Department of Mechanical Engineering at Vanderbilt University , with an anticipated start in Spring 2027 . The positions span two research tracks: Computational Fluid Dynamics with Scientific Machine Learning and Scientific Machine Learning for Fluid Dynamics . Topics include high-order numerical methods, DGSEM, compressible and high-speed flows, adaptive and high-performance computing, ML-assisted solvers...