PhD Position in Modeling and Control of Nonlinear Dynamical Systems from Data
Develop advanced spectral submanifold methods for interpretable, data-driven nonlinear modeling and control in complex physical systems.
Best for:Best for applicants with a strong mathematical foundation and research experience in nonlinear dynamical systems, fluid mechanics, or control theory, seeking to develop novel data-driven modeling techniques.
Overview
This PhD position at ETH Zürich focuses on advancing spectral submanifold (SSM) methods to create theoretically robust, interpretable alternatives to black-box neural networks for modeling nonlinear dynamical systems. The work will explore applications in fluid-structure interactions, soft robotics, and turbulent flows, among others. The candidate will collaborate within the Chair in Nonlinear Dynamics, contributing to both fundamental research and practical engineering challenges. The position offers flexibility in departmental placement (Mechanical Engineering or Mathematics) and a flexible start date, emphasizing interdisciplinary collaboration and innovation in data-driven modeling.
What you'll do
- Develop and refine spectral submanifold (SSM) methods for nonlinear model reduction, aiming for theoretically sound, interpretable, and computationally efficient solutions.
- Investigate and apply nonlinear modeling and control approaches to complex physical systems such as fluid-structure interactions, soft robotics, and turbulent flows.
- Conduct research aligned with ongoing projects in the Chair in Nonlinear Dynamics, contributing to both fundamental theory and practical applications.
- Collaborate with interdisciplinary teams to translate theoretical advancements into actionable engineering solutions.
- Present research findings at conferences and publish results in high-impact academic journals.
- Participate in academic and professional development activities offered by ETH Zürich.
Requirements
Degree required: Master's degree in mechanical engineering, applied mathematics, physics, or a related field
Degree offered: PhD
Language: English; proficiency sufficient for academic research and collaboration
Instruction: English
- Strong mathematical skills, evidenced by high academic performance
- Prior research experience in fluid mechanics, structural vibrations, model reduction, or control theory
- Proficiency in nonlinear dynamical systems methods and data-driven analysis techniques
- No explicit nationality or residency restrictions mentioned
- No age or prior experience caps specified
Funding & terms
How to apply
Applicants must submit their application through ETH Zürich’s online application portal. The required documents include a CV, Bachelor and Master’s transcripts, and contact information for at least two references. Applications via email or postal services will not be considered.
- CV
- Bachelor’s transcripts
- Master’s transcripts
- Contact information of at least two references
Contact
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