PhD opportunity, project description
Events cluster in time and space: tweets go viral, neighbourhoods experience crime waves, earthquakes induce aftershocks. Temporal and spatial proximity are major factors in the chain reaction of events, as are the structured networks on which they occur. Yet, the nature of how and why these patterns of events propagate is much more complex.
This project will focus on developing a suite of self-exciting point process models. There will be a particular focus on incorporating adequate correction methods for edge-effects and on the development of robust model diagnostic tools for such a framework. You will also aid in extending existing open-access software and in the development of computationally efficient methods to fit such models.
Required Skills
- Experienced use of the statistical software R
- Point process and other spatiotemporal modelling experience
- Knowledge of & experience with a range of approximation techniques
- Knowledge of & experience with Bayesian techniques
- Use of version control software (preferred)
Eligibility The applicant must meet the University of Auckland’s doctoral entry requirements.
Contact If you have any questions about the project and/or wish to apply please contact Dr Charlotte Jones-Todd at c.jonestodd@auckland.ac.nz
Funding This project is part of the 2021 Marsden award 21-UOA-058 and in line with this, the position comes with an NZD $35,000 base stipend + tuition fees per annum for 3 years.
