PhD student in Autonomous Velocimetry for Fluid Mechanics

Materials science and technology are our passion. With our cutting‑edge research, Empa's around 1,100 employees make essential contributions to the well‑being of society for a future worth living. Empa is a research institution of the ETH Domain.

Optimizing vehicle aerodynamics to reduce transportation emissions, understanding airborne disease transmission, and predicting climate‑related transport phenomena all require precise knowledge of fluid flow dynamics. Advanced experimental methods such as Particle Image Velocimetry (PIV) and 3D Lagrangian Particle Tracking (LPT) provide crucial insights.

In this project, you will contribute to the development of AI‑driven methodologies for experimental fluid mechanics, focusing on:

• Designing multi‑fidelity neural networks for adaptive flow reconstruction, enabling both real‑time coarse diagnostics and high‑fidelity offline velocity field estimation.
• Developing reinforcement learning (RL) algorithms...