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PhD Position in Machine Learning Applications for Predictive Maintenance

ETH Zurich is pleased to invite applicants to apply for a PhD position. This fellowship is available for all students around the world. Applicants should apply as soon as possible.

The newly founded Chair of Intelligent Maintenance Systems at the Department of Civil, Environmental and Geomatic Engineering at ETH Zurich focuses on developing algorithms and decision support systems for data-driven intelligent maintenance of industrial assets. We are inviting applications for a new position. Digitalization of industrial assets is enabling the capture and the real-time transmission of information on system condition. The collected data is nowadays of varied nature, including images and video streams and increasingly massive, potentially resulting in much better information on system condition. Yet, these recent changes drive traditional model- and knowledge-based approaches too difficult to implement and too demanding in resource usage. This project will tackle the challenge of effectively using the diverse, high-dimensional, high-frequency condition monitoring data of industrial assets to improve availability and resilience of the assets. The main objective of the PhD project is to develop a deep-learning framework that will enable (a) learning fault signatures from heterogeneous condition monitoring data sources, (b) transferring them between different systems of the same fleet and © predicting the remaining useful life based on the learned fault signatures and their predicted evolution in time.

We are looking for a highly motivated candidate holding a Master's Degree in engineering, physics, applied mathematics, computer science or related fields. The successful candidate has strong analytical skills, is proactive, self-driven with strong problem solving abilities and out-of-the-box thinking. Moreover, programming experience, preferably in Python, is expected. Experience in predictive maintenance, machine and deep learning is beneficial. Professional command of English (both written and spoken) is mandatory and knowledge in German is beneficial. You enjoy working in an interactive international environment with other doctoral students and post-docs, referring continuously to practical problems and solutions and collaborating with industrial project partners.


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