PhD: Data-Driven Nonlinear Dynamics & Control

ETH Zurich; Schweiz; On-site; CHF 60,000 - 80,000; Part time

Benefits offered by this job

Flexible start date

Job summary

ETH Zürich's Chair in Nonlinear Dynamics invites applications for a 100% PhD position in modeling and control of nonlinear dynamical systems from data. The project aims to provide fast, theoretically sound, interpretable modeling alternatives to black-box neural networks.

Based at the Department of Mechanical and Process Engineering or the Department of Mathematics, the PhD focuses on spectral submanifold methods, data-driven model reduction, and potential applications in fluids, structures, and

Qualifications

• Master's degree in mechanical engineering, applied mathematics, physics, or related areas.
• Strong mathematical skills (evidenced by high grades) and analytical thinking.
• Prior research experience in fluid mechanics, structural vibrations, model reduction or control is advantageous.
• Experience with nonlinear dynamical systems methods and data-driven analysis is a plus.

Responsibilities

• Develop and apply nonlinear dynamical systems methods to data for physical problems.
• Advance spectral submanifold (SSM) methods and nonlinear model reduction.
• Explore nonlinear modelling and control for fluid-structure interactions, materials with memory, soft robotics, and related areas.

Job description

ETH Zürich's Chair in Nonlinear Dynamics invites applications for a 100% PhD position in modeling and control of nonlinear dynamical systems from data. The project aims to provide fast, theoretically sound, interpretable modeling alternatives to black-box neural networks.

Based at the Department of Mechanical and Process Engineering or the Department of Mathematics, the PhD focuses on spectral submanifold methods, data-driven model reduction, and potential applications in fluids, structures, and