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Multiple Spreading Processes in Real-World Dynamic Complex Networks

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

We need to challenge current trends and existing approaches as well as promoting new, sometimes controversial and maybe even bold ideas for analysis of spreading processes in complex networks.

For decades we tried to understand the spreading processes in complex networks and although the progress has been impressive, and we managed to discover many of the rules that govern diffusion processes over the network, we are very far from understanding such concepts as spread in multilayered networks, multiple spreads (competing or supporting) over complex network, external factors and their role in the diffusion processes, how spreading processes depends on and influence network structure, diffusion in dynamical networks.

The main goal of the project is to propose, develop and evaluate new methods to model and predict the behaviour of Multiple Spreading Processes in Real-World Dynamic Complex Multilayer Networks.
Key elements to consider are: (i) increasing complexity and size of real-world networked structures and their nowadays common multilayered character that do not fit existing network models anymore and (ii) increasing complexity, number of spreads and nature of interactions between spreads that can exist within one network.
There is a need for reshaping the landscape of diffusion phenomenon in complex networks, and if you think that this is something you want to do then please apply for this PhD scholarship.


Supervisors: Katarzyna Musial-Gabrys (University of Technology Sydney) and Piotr Brodka (Wroclaw University of Science and Technology, Poland)

Before you apply and for more info, please contact Katarzyna Musial-Gabrys at katarzyna.musial-

How To Apply Guide: uts/how-apply

Funding Notes

Stipend value $27,082 pa (tax-exempt); only full-time, 3 years.

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