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PhD position in reinforcement learning for optimal fault mitigation and recovery actions in the operation of complex industrial assets in Zürich

This research group is looking for you!

Jobbeschreibung

ETH Zurich is one of the world’s leading universities specialising in science and technology. It is renowned for its excellent education, its cutting-edge fundamental research and its efforts to put new knowledge and innovations directly into practice. The Chair of Intelligent Maintenance Systems at the Department of Civil, Environmental and Geomatic Engineering focuses on developing algorithms and decision support systems for data-driven intelligent maintenance of industrial assets.
Predicting the remaining useful life of a system or a component enables taking preemptive mitigating actions, thereby reducing the downtime and improving the system reliability and availability. Yet, there is a set of different actions that can be taken if the remaining useful life of a system is known, including maintenance actions aiming to prolong the remaining useful life or preemptive replacements of the component. However, a preemptive replacement at the end of the remaining useful life may not be the optimal action in terms of system performance. A more efficient use of the knowledge on the fault evolution in time is to use this information for proactive control of the remaining useful life and the system performance. The project aims at developing reinforcement-learning approaches for optimal fault mitigation and system health management. A collaboration with the Prognostics Center of Excellence (PCoE) at NASA Ames Research Center is foreseen for this project.
We look forward to receiving your online application including a letter of motivation, CV, a brief statement of research interests (1 page), transcripts of all obtained degrees (in English), one publication (e.g. thesis or conference/journal publication: the one that you consider being most relevant to the position that you are applying for), and contact details of two referees. Only complete applications containing all the required documents will be considered. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

For more information about the chair, please visit: . Questions regarding the position should be directed to Prof. Dr. Olga Fink by email ofink@ethz.ch (no applications).

Veröffentlicht am

29-02-2024

Extra Informationen

Status
Inaktiv
Standort
Zürich
Tätigkeitsbereich
Baugewerbe, Pädagogik / Nachhilfe
Führerschein erforderlich?
Nein
Auto erforderlich?
Nein
Motivationsschreiben erforderlich?
Nein