ARC PhD Scholarship ($31,885pa): Switching Dynamics Approach for Distributed Global Optimisation

ARC PhD Scholarship ($31,885pa): Switching Dynamics Approach for Distributed Global Optimisation

https://www.rmit.edu.au/students/student-essentials/information-for/research-candidates/enriching-your-candidature/grants-and-scholarships/postgraduate-by-research/switching-dynamics-approach-distributed-global-optimisation

Fast growing big-data in industrial systems makes finding optimal solutions for timely decision making more difficult. This project aims to create a breakthrough switching dynamics approach and new technology to speed up finding optimal solutions. It will develop a distributed switching dynamics based optimisation scheme for global optimisation problems in big-data environments, hence resulting in a practical technology for industry applications (e.g. smart grids).

The specific objectives of this Project are:

1. Establish a switching dynamics approach for global optimisation, forming the foundation to accelerate convergence to search for optimal solutions.

2. Create an intelligent distributed global optimisation scheme with switching dynamics based multi-agent system concepts, which is scalable to big-data optimisation tasks.

This is a project funded by an Australian Research Council (ARC) Discovery Grant for three years (2021-2023), which aims to develop a breakthrough switching dynamics approach and new technology for global optimisation tasks in big-data applications.

The successful applicant will work on this project for the PhD in the School of Science at RMIT University supervised by Prof. Andrew Eberhard and carried out in collaboration with Prof. Xinghuo Yu (Electrical Engineering) at RMIT.

Qualifications

You are required to have a Bachelor degree in a relevant discipline such as Mathematical Sciences or Electrical Engineering with at least 2nd class upper honours or equivalent.  Experience in one or more areas in Nonlinear Dynamical Systems, Discontinuous Control Systems, Optimisation theory and\or Optimisation Algorithms is desirable. The applicant must have a strong background in mathematics.

Application

A CV detailing your qualifications, research experience and achievements, a statement of your suitability to this project, and contact details of two referees are to be emailed to Professor Andrew Eberhard at andy.eberhard@rmit.edu.au.  For further information, please contact Prof. Andrew Eberhard directly.