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Time Series Representation Learning for Industrial Process Characterization

Posted on 22 Oct 2026

Employer

University of Leuven, Leuven, Belgium

Description

The M-Group at KU Leuven Bruges Campus is an interdisciplinary research team focusing on intelligent and dependable mechatronic systems, combining research expertise from the departments of Computer Science, Electrical Engineering and Mechanical Engineering. One of the key research tracks focusses on the application of Artificial Intelligence and Machine Learning in real-world industrial settings on the one hand. The objective of the proposed PhD position is to investigate how novel techniques for time series representation learning on sensor data origination from complex and dynamic industrial processes can be leveraged for process characterization across multiple time series data mining tasks, such as anomaly detection, anomaly diagnosis and root cause analysis. The successful candidate will be offered to opportunity to pursue a PhD in Computer Science at KU Leuven, and will also be embedded within the Declarative Languages and Artificial Intelligence (DTAI) lab (https://dtai.cs.kuleuven.be), which pursues excellence in an explicit and synergistic combination of fundamental and applied research on machine learning and artificial intelligence. Doctoral training is provided in the framework of the Leuven Arenberg Doctoral School (https://set.kuleuven.be/phd). The PhD will be supervised by Prof. Mathias Verbeke and Mr. Louis Carpentier.

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