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that reduce raw data at the sensor level. You will develop AI and machine learning algorithms for anomaly detection, pattern recognition, and efficient data compression. To ensure practical usability
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15 Nov 2025 Job Information Organisation/Company KU LEUVEN Research Field Engineering » Mechanical engineering Engineering » Materials engineering Engineering » Industrial engineering Technology
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machine learning algorithms for anomaly detection, pattern recognition, and efficient data compression. To ensure practical usability, these models will also be optimized to run efficiently on edge hardware
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classification. To study how to incorporate expert feedback into a semi-supervised learning model, and how to efficiently compress and run the model on embedded devices. To combine heterogeneous data streams
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. This will involve investigating techniques for model compression and efficient inference to enable on-board condition monitoring directly at the wind turbine, reducing data transmission requirements, central