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The successful candidate will study the spread of contagion on networks through the following focus areas:
Dynamical models: Developing realistic models for the spread of diseases and ideology on networks, particularly higher-order networks
Bayesian Inference: Reconstructing networks and disease dynamics from imperfect and noisy observational data
Higher-order network structure: Developing higher-order measures sensible for the spread of diseases and information
Software development: Developing scientific Python software to support research and facilitate the dissemination of results
The candidate will also have considerable freedom to tackle any related topics of interest.