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

, 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 for a multi-agent robotics system that autonomously optimizes 3D velocimetry measurements by dynamically adjusting camera positions and optical parameters. 
• Integrating the framework within a digital twin environment for pre-training and simulation-based optimization, enabling autonomous measurement campaigns and real-time data assimilation.

This research combines

to establish the foundation for the next generation of

in complex flow environments.

We are looking for 2 highly motivated

with a strong analytical background and an MSc degree in

The candidates should have: 

• Solid programming skills (Python, MATLAB, or C++). 
• Knowledge of the OpenCV library. 
• Strong interest in machine learning, reinforcement learning, and fluid dynamics. 
• Ability to work independently and collaboratively in an interdisciplinary team. 
• Excellent command of English, both written and spoken. 
• Experience with experimental fluid mechanics and computer vision is an advantage.

We offer a

within the ETH Domain, with close collaboration between Empa, ETH Zürich, and other international research partners. Empa provides

and strong support for personal and professional development. The PhD student will be enrolled in the

, depending on academic affiliation. The position is available immediately or upon agreement.

For further information about the position, please contact:

, Scientist and Principal Investigator, or

, Head of Laboratory for Computational Engineering.

We live a culture of inclusion and respect. We welcome all people who are interested in innovative, sustainable and meaningful activities - that's what counts.

PatriciaNitzsche, Stv. Leiterin Human Resources / Dep. Head Human Resources