PhD in Physics-Informed Graph Neural Networks for Wind Turbine Health Monitoring École polytechnique fédérale de Lausanne in Switzerland

EPFL’s IMOS Lab is advertising a PhD position in Physics-Informed Graph Neural Networks for Wind Turbine Health Monitoring. The project sits at the intersection of computer science, physics, and mechanical engineering, with a strong focus on data-driven methods for predictive maintenance and structural/asset health monitoring in renewable energy systems.

The position is associated with Olga Fink, Assistant Professor of Intelligent Maintenance and Operations Systems at EPFL. The research topic suggests work on graph neural networks, physics-informed machine learning, and condition monitoring for wind turbines, likely involving sensor data, diagnostics, and reliability-oriented modeling.

This is a PhD opening at École polytechnique fédérale de Lausanne (EPFL) in Lausanne, Switzerland. The post does not mention a deadline, stipend amount, or detailed eligibility criteria in the excerpt provided. It does indicate that applicants should be highly motivated.

Interested candidates should review the official EPFL careers page and apply through the job portal linked in the post. The LinkedIn post also points to the same opportunity for additional context.