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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
predictive models for complex multi-physics dynamical systems as well as towards designing observer-based state estimators from output timeseries data measurements. The research also involves development
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for sequential data modelling, including Physics-informed Machine Learning and Koopman Operator-based representation framework, towards building interpretable predictive models for complex multi-physics dynamical
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generations of research and development professionals, data specialists, technology experts, inventors, and scientists for industry and society. NANO group at the Department of Applied Physics, is seeking
Searches related to complex systems physics
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