PhD Position Spread in Networks – DelftUniversityofTechnology(TUDelft) – Delft

  • Delft


Epidemic processes widely apply to biological and computer network viruses, to cascading failures in power grids, to the spread of news, rumour or emotions in a social network, to transactions in banking networks and to the processing of functions and movements in the human brain. An epidemic process spreads over an underlying network topology or contact graph, that is generally changing over time. Standard models used so far are mostly based on Markovian processes and mean-field approximations. As the recent panic caused by Credit Suisse and Silicon Valley Bank throughout the global banking system has shown, dramatic improvements in modelling spread in networks is crucial to better understand and respond to such crises. As a PhD student at TU Delft, you will conduct research and develop non-Markovian models from the viewpoint of Network Science and geared to predicting and preventing spread in networks.

Depending on your interests in an epidemic application domain, your research may be dedicated to data communications, energy networks, and even pandemics within the scope of the ERC ViSioN project. Once you have mastered the theory, you will build models, describing the natural phenomenon with mathematical precision. Beside deriving theory and collecting data of real-world epidemic spread to validate your model, you will also program your model. Your software will convince decision makers of realistic scenarios and help reduce response times. You will be building your network of relevant stakeholders, in industry, among academics or at university hospitals. As a PhD student, you will also be coaching and supervising Master students with their thesis projects.

You will be joining the diverse and driven team of academic staff, PhD students and postdocs of the <a Architectures and Services Group. We share a drive to understand the characteristics of and processes running on complex networks, ranging from man-made infrastructures to biological, brain and social networks. Fostering an inspiring, friendly and supportive environment, we meet regularly and share ideas and knowledge. You will receive all the training you need to evolve as a scientist.

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