[ML-news] [Job][PhD positions] PhD Student in (multi-agent) reinforcement learning for health-aware control at IMOS Lab - EPFL

[Olga Fink]

We are looking for a highly motivated PhD student in (𝐦𝐮𝐥𝐭𝐢-𝐚𝐠𝐞𝐧𝐭) 𝐫𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐟𝐨𝐫 𝐡𝐞𝐚𝐥𝐭𝐡-𝐚𝐰𝐚𝐫𝐞 𝐜𝐨𝐧𝐭𝐫𝐨𝐥 at the IMOS Lab - EPFL as part of an ERC Consolidator Grant.

Project description

The objective of this project is to develop novel methodologies based on (multi-agent) reinforcement learning for health-aware control of complex engineering systems. The research will focus on integrating system health and degradation dynamics into control strategies, enabling decision-making that jointly optimizes performance and long-term asset reliability.

The project will explore how reinforcement learning agents can learn control policies that account for operational objectives, physical constraints, and system aging, with a particular emphasis on multi-agent settings where multiple subsystems interact. Physics-informed models and data-driven approaches will be combined to ensure that learned policies are both efficient and consistent with underlying system dynamics.

Applications will include complex industrial and energy systems (e.g., wind turbines or other large-scale infrastructure), where control decisions have a direct impact on system lifetime.

This PhD position is part of an ERC Consolidator Grant, supporting cutting-edge research on health-aware control and intelligent maintenance of complex systems.

Profile

We are looking for a PhD candidate with a strong analytical background, and an outstanding MSc degree in Engineering, Control, Computer Science, Physics, Applied Mathematics, or a related field.

 

You should have a solid foundation in machine learning and control, ideally with experience in reinforcement learning, optimization, or dynamical systems. Knowledge of deep learning, signal processing, or physics-informed modeling is considered a strong asset.

We expect the candidate to be self-driven, with strong problem-solving abilities and out-of-the-box thinking. Professional command of English (both written and spoken) is mandatory. 

🔗 Apply here: application link (Please submit  a letter of motivation; a CV, brief research statement (one page) describing your project idea in the field of reinforcement learning and health-aware control, making connections to your experience and related work from the literature, transcripts of all obtained degrees (in English), one publication (e.g. thesis or preferably a conference or journal publication, a link is sufficient)

 

Only applications submitted via the EPFL application platform will be accepted (no applications by email)

 

 

----------------------------------

Prof. Dr. Olga Fink

Laboratory of Intelligent Maintenance and Operations Systems

GC A3 424 (Bâtiment GC)
Station 18
CH-1015 Lausanne