Olga Fink
5 months ago
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PhD in Physics-Informed Graph Neural Networks for Wind Turbine Health Monitoring École polytechnique fédérale de Lausanne in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
Funding details are not specified in the post excerpt.
Deadline
Expired
Country
Switzerland
University
École Polytechnique Fédérale de Lausanne

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About this position
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.
Funding details
Funding details are not specified in the post excerpt.
What's required
Highly motivated PhD candidate. Interest in physics-informed graph neural networks, wind turbine health monitoring, and related machine learning or engineering topics is implied; no further formal requirements are stated in the post excerpt.
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