Integrating data-driven methodologies and model reduction for the control of complex networks at University of Auckland on FindAPhD.com

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Dr Lauren Smith Applications accepted all year round Funded PhD Project (Students Worldwide)

Auckland New Zealand Applied Mathematics Control Systems Data Analysis Mathematical Modelling Networks Computer Science Engineering Physics

About the Project

This PhD project will combine data assimilation and model reduction methodologies to predict and control functional failures on complex networks, such as catastrophic blackouts in power grids. The data assimilation methods developed will recover unknown model parameters in coupled oscillator networks. Model reduction methods will be developed for coupled oscillator systems with interactions beyond pairwise coupling. These model reduction methods will allow a deeper understanding of the system dynamics, as well as significantly reducing the computational cost of network diagnostics and network control algorithms.

The ideal candidate will have skills or experience in:

* Dynamical systems

* Data-driven methodologies

* Scientific computer programming

Applicants should have or expect to receive a BSc(Hons) or MSc or equivalent in mathematics.

The ideal start date is early 2024, but is flexible.

Applications including a CV, academic transcript, and cover letter should be sent directly to Lauren Smith.

Funding Notes

The project is fully funded by the Royal Society of New Zealand. It covers all tuition fees for international and domestic students and includes a tax-free stipend of NZ$35,000 annually for up to three years.