The research will involve theoretical work in information theory and network science, as well as computer agent-based simulations. It will study fragility of modern civil infrastructure networks under stress, aiming to develop methods improving their resilience in the face of failures cascading through interdependent transport, communication and power networks. The PhD will be supervised by Prof. Mikhail Prokopenko. The applicant will join the Complex Systems Research Group (CSRG) at The School of Civil Engineering – The University of Sydney. The CSRG group comprises ten academics, and has wide collaborations across the University, Australia, and internationally. It is a vibrant, world-leading group in the fields of guided self-organisation and critical phenomena forecasting.
Traditionally, complex systems have been mainly modelled and analysed as single networks that do not interact with or depend on other networks. No systematic computational and mathematical framework is currently available to adequately address the consequences of disruptions and failures occurring simultaneously in interdependent critical infrastructures. This PhD study will develop novel methods to model interdependent networks, and crucially, interdependent cascades of failures, where the failure of nodes in one network generally leads to failures of dependent nodes in other networks, which in turn may cause further damage to the first network. This will include methods to predict critical phenomena exhibited by interdependent networks, such as tipping points and phase changes. Phase transitions in average network damage will be analysed with respect to several concurrent capacities: power-transmission, transport, and communication, and related to the heterogeneity in transmission, transport, and communication capacities across several networks.
Applicants need to satisfy the eligibility criteria for PhD enrolment at The University of Sydney. Backgrounds in applied mathematics, physics, computer science, and specifically in information theory, complex networks and statistical mechanics will be beneficial. The successful applicant will demonstrate a strong commitment to academic research in the proposed field. He/she will have excellent written and oral communication skills, as well as demonstrated ability to program in MATLAB, Java, or C++, and will be willing to create and develop original approaches to tackle open questions. Applications should be sent by email to Prof. Mikhail Prokopenko: firstname.lastname@example.org They should include a Resume and a Cover Letter. In their Cover Letter, applicants are invited to include a short (about 250 words) research statement explaining how they understand the issues related to the topic of research.
The opportunity ID for this research opportunity is 1946