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.

The in Dübendorf is offering a position for two motivated doctoral students.

PhD student in Autonomous Velocimetry for Fluid Mechanics

Your tasks

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 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 fluid mechanics, artificial intelligence, and robotics to establish the foundation for the next generation of autonomous experimental diagnostics in complex flow environments.

Your profile

We are looking for 2 highly motivated PhD students with a strong analytical background and an MSc degree in Mechanical or Aerospace Engineering, Physics, Computational Science, or a related discipline.

The candidates should have :

Our offer

We offer a stimulating, multidisciplinary research environment within the ETH Domain, with close collaboration between Empa, ETH Zürich, and other international research partners. Empa provides state-of-the-art experimental and computational infrastructure, internationally competitive employment conditions, and strong support for personal and professional development. The PhD student will be enrolled in the ETH Zürich / University of Zürich doctoral program , depending on academic affiliation. The position is available immediately or upon agreement.