The Eindhoven University of Technology invites applications for a PhD position in machine learning for predictive maintenance.
About the position:
This position is funded by the EU-funded project Cyber Physical System based Proactive Collaborative Maintenance (MANTIS), which explores predictive maintenance in the contexts of factory automation and servicing of health care scanning equipment.
Our focus in this project is on applying machine learning techniques to identify patterns in the sensor data corresponding to component failures for predicting system failures. In particular, we are interested in exploring data-driven methods for root cause failure analysis, remaining useful life identification of wearing components, and failure prediction on component and system level. In this project, we cooperate with Philips Consumer Lifestyle and Philips Health Care, who provide industrial use cases in factory automation and servicing of health care scanning equipment, which will support our research and validate our research results.
We are seeking talented, enthusiastic candidates with excellent analytical and communication skills holding a university degree (MSc) in Computer Science, Applied Mathematics, Operations Research, or similar. A strong interest in data driven applications is essential. Experience in machine learning, data mining, process mining, optimization, or statistics is of benefit.