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Doctoral Candidate in Digital Twins for Wind Turbines
1 semana atrás
As a Doctoral Candidate (DC) in this project, you will have the opportunity to work on advanced operational and maintenance strategies for wind turbines, leveraging machine learning and digital twin technologies.
The position involves developing innovative data-driven approaches to enhance turbine performance and reliability, and creating explainable frameworks for predictive maintenance, utilizing SCADA data to identify potential component failures. Additionally, you will design and implement digital twin frameworks that integrate real-time data for continuous health monitoring of wind turbines and their components.
The role also involves developing probabilistic models to assess turbine fatigue and predict their remaining operational lifespan. By blending physics-based and data-driven techniques, you will support efforts to extend the turbines' operational life, contributing to the sustainability of wind energy systems.
We are looking for a highly skilled individual with expertise in machine learning and digital twin technologies, as well as strong communication and teamwork skills. The ideal candidate will have experience in computer science and/or data science, and will be proficient in the English language.
- Strong problem-solving skills
- Ability to work under deadlines
