PhD Student in (Multi-Agent) Verstärkung Lernen für gesundheitsbewusste Kontrolle — EPFL
CHF 60'500 - 91'500
EPFL · Lausanne (VD)
- Ort
- Lausanne
- Vertrag
- full-time
- Veröffentlicht
- vor 47 Tagen
LohnCHF 60'500 - 91'500
Rollenüberblick
IMOS The Intelligent Maintenance and Operations Systems (IMOS) Lab at EPFL is looking for a motivated and out-of-the-box thinking PhD researcher, (100%, in Lausanne, fixed-term) starting in September or upon agreement.
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.
- IMOS The Intelligent Maintenance and Operations Systems (IMOS) Lab at EPFL is looking for a motivated and out-of-the-box thinking PhD researcher, (100%, in Lausanne, fixed-term) starting in September or upon agreement.
- 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.
Bewerbungsprozess
- 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.
- Work Environment EPFL is one of the most dynamic university campuses in Europe, ranks among the top 20 universities worldwide and offers an exceptional working environment with very competitive salaries.
- The IMOS Lab ( https://www.epfl.ch/labs/imos/ ) offers a highly motivating, interdisciplinary scientific environment with many opportunities to interact across projects and researchers, and maintains an excellent network of collaborations with industrial stakeholders and leading international universities.
- 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.
Weitere Details
- Professional command of English (both written and spoken) is mandatory.
- Application process Formal applications including: a letter of motivation, a CV of the candidate,
Notizen und Originalinhalt
- Application process Formal applications including:
- a letter of motivation,
- a CV of the candidate,
