Job Description

Application of reinforcement learning (RL) to mitigate dynamic stall using a numerical method. The project builds on our prior work, where RL is used to control flow around a circular cylinder (JFM 932, A44, 2022), and the open-source software from that work will serve as the starting point. The final outcome will be a functioning simulation that shows how intelligent, adaptive control can reduce stall, improve aerodynamic performance, and provide deeper insights into the physics of unsteady airflows.

Qualifications

(1) PhD in applied mathematics, mechanical engineering, computer science

(2) Experience in Python, Matlab and DNS (direct numerical simulations)

(3) Able to work independently and efficiently

More Information

Location: Kent Ridge Campus

Organization: College of Design and Engineering

Department : Mechanical Engineering

Employee Referral Eligible: No

Job requisition ID : 29263