PhD: Explainable Time Series Learning for Industry 4.0

KU Leuven; West-Vlaanderen; On-site; EUR 27,000 - 31,000; Full time

Job summary

KU Leuven, Bruges Campus, invites applications for a fully funded PhD position in the M-Group within the DTAI Lab. The project focuses on automatically learning explainable representations from high-dimensional industrial time series data and applying them to anomaly detection, diagnosis, and root cause analysis.

You will pursue a PhD in Computer Science at KU Leuven, supervised by Prof. Mathias Verbeke and Mr.

Qualifications

• Master's degree in Computer Science, Artificial Intelligence, Electrical Engineering, Mathematical Engineering or related field.
• Proficient in written and spoken English.
• Experience with machine/deep learning; time series analysis is a plus.
• Proficient in Python and data science toolkits.

Responsibilities

• Develop explainable representations from high-dimensional industrial time series data.
• Design algorithms for mining motifs in multivariate time series and learning relationships among motifs.
• Balance scalability and representativeness of motif-based representations.
• Collaborate with domain experts and supervisors to steer research directions.

Skills

English proficiency

Machine learning

Python

Time series analysis

Research planning

Education

Master's degree in Computer Science or AI

Tools

Python

Job description

KU Leuven, Bruges Campus, invites applications for a fully funded PhD position in the M-Group within the DTAI Lab. The project focuses on automatically learning explainable representations from high-dimensional industrial time series data and applying them to anomaly detection, diagnosis, and root cause analysis.

You will pursue a PhD in Computer Science at KU Leuven, supervised by Prof. Mathias Verbeke and Mr.