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ETH Zürich invites applications for a 100% PhD position in the development and application of nonlinear dynamical systems methods from data. The goal is to deliver fast, interpretable alternatives to black-box neural networks, with emphasis on spectral submanifold methods and nonlinear model reduction.
The successful candidate will work across the Department of Mechanical and Process Engineering or the Department of Mathematics, with a flexible start date and a strong emphasis on rigorous theory
ETH Zürich invites applications for a 100% PhD position in the development and application of nonlinear dynamical systems methods from data. The goal is to deliver fast, interpretable alternatives to black-box neural networks, with emphasis on spectral submanifold methods and nonlinear model reduction.
The successful candidate will work across the Department of Mechanical and Process Engineering or the Department of Mathematics, with a flexible start date and a strong emphasis on rigorous theory