Research Fellow, Mechanical Engineering
This project is to develop data-driven machine learning-based models for prediction of aerodynamic performance and optimization of two-element airfoil shapes. Numerical verification will be made by computational fluid dynamics.
The proposed project extensively involves mathematical modelling, computer programming, and numerical simulation. It requires researchers to have strong background in mathematics and computational physics. The candidate must have a PhD degree and experiences in computational fluid dynamics and machine learning related area. The candidate should be able to write computer codes for prediction and optimization.
Location: Kent Ridge Campus
Department : Mechanical Engineering