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Olga Fink

5 months ago

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

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Country

Switzerland

University

École Polytechnique Fédérale de Lausanne

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Keywords

Computer Science
Machine Learning
Mechanical Engineering
Electrical Engineering
Energy Engineering
Physics

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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