Postdoctoral Researcher – Iterative Learning Control of Industrial Systems

Eidgenössische Technische Hochschule Zürich

Zürich

Vor Ort

CHF 80.000 - 100.000

Vollzeit

14 Tage+
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Zusammenfassung

Eidgenössische Technische Hochschule Zürich, in collaboration with inspire AG, is offering a Postdoctoral Researcher position focused on Iterative Learning Control of Industrial Systems. The role involves developing cutting-edge algorithms for real-world industrial applications, emphasizing collaboration with industry partners.

The ideal candidate will hold a PhD in robotics or engineering and possess strong theoretical and practical expertise. The position starts in October 2026.

Qualifikationen

  • Strong understanding of learning‑based control methods.
  • Excellent foundation in optimization and control theory.
  • Hands-on experience with industrial control systems is a plus.

Aufgaben

  • Develop customized ILC and parameter optimization algorithms.
  • Implement and test algorithms on real systems.
  • Collaborate closely with industry partners.

Kenntnisse

Learning-based control methods
Iterative learning control theory
Linear algebra
Numerical methods
Optimization
Control theory
Industrial control systems

Ausbildung

PhD degree in robotics, electrical or mechanical engineering, or CS

Jobbeschreibung

Postdoctoral Researcher – Iterative Learning Control of Industrial Systems

inspire AG is the leading Swiss competence centre for product innovation and advanced manufacturing. As a strategic partner of ETH Zurich, our mission is to transfer knowledge and technology from research to Swiss machine, electrical and metal industries.

The research group Control and Automation at inspire AG offers the following postdoctoral position as part of an industrial collaboration with a Swiss industry partner, and the Automatic Control Laboratory (IfA) at ETH Zurich.

Planned start date for the position is October 2026.

Project background

Our research group works on increasing the efficiency of industrial systems in real-world deployment by enabling process monitoring, learning, and policy training while ensuring safety and efficiency. For this, we develop novel learning-based control methods with practical applicability and theoretical guarantees.

We're looking for a skilled Postdoctoral Researcher to develop and deploy cutting‑edge Iterative Learning Control (ILC) algorithms on real‑world industrial platforms. The project requires good theoretical and hands‑on expertise. Perfectly suited for those at the intersection of theory and application.

  • Develop customized ILC and parameter optimization algorithms for industrial applications, going from theoretical analysis to implementation and testing on real systems
  • Develop adaptive control and estimation schemes to support hardware implementation
  • Collaborate closely with our industry partner to solve unique problems
Profile
  • PhD degree in robotics, electrical or mechanical engineering, CS, or relevant fields
  • Solid understanding of learning‑based control methods and knowledge of iterative learning control theory with applications to industrial systems
  • Excellent foundation in linear algebra, numerical methods, optimization, and control theory
  • Background in online optimization theory and adaptive control theory is a plus
  • Hands‑on experience with industrial control systems is a plus
  • An excellent knowledge (written/oral) of English is a must. Knowledge of German is beneficial
  • Highly self‑organized and structured way of working and solution orientation
  • High motivation and willingness to learn new skills
  • High level of teamwork, positive work attitude and creativity
  • Willingness to supervise and support student projects
We offer

We offer a full‑time position for a postdoctoral researcher in our group as part our industrial collaboration project. Through the close cooperation with our project partner, you will quickly establish contacts to industry. In our young team you will work at the forefront of today's knowledge in learning‑based industrial control.

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