PhD in spatial statistics

We would like to announce a new PhD scholarship opportunity in spatial statistics, linked to here, and summarised below:

https://www.stats.otago.ac.nz/?MarsdenPhD

 

Research project: “A new generation of statistical models for spatial point process data”; 19-UOO-191.

Funding body: Royal Society of New Zealand Marsden Fund

Funding duration: March 2020 – March 2023

Supervisory team:

Dr Tilman Davies (PI — University of Otago, New Zealand);

Prof Martin Hazelton (AI – University of Otago, New Zealand);

Prof Adrian Baddeley (AI – Curtin University, WA, Australia).

 

We are currently seeking expressions of interest for a fully-funded 3-year PhD scholarship, available as part of a prestigious Royal Society of New Zealand Marsden Fund Research Grant recently awarded in the 2019 round. The student will be supervised by Principal Investigator Dr. Tilman Davies alongside Professor Adrian Baddeley and Professor Martin Hazelton, working on their project “A new generation of statistical models for spatial point process data” (19-UOO-191). The scholarship provides a generous annual tax-free stipend and student fees are also covered.

 

The research project develops new methods for disentangling fixed and random effects in spatial point patterns. This is a fundamental and important problem in the interpretation of data in a wide variety of research fields, including epidemiology, ecology, and archaeology to name a few. In the absence of solution to this problem, researchers are unable to prove whether a cluster of disease cases, for example, is explained by a single contaminating source or by contagion between infected individuals.

 

The student, based primarily at the University of Otago in Dunedin, New Zealand, will work closely with the supervisory team to develop new and refine existing approaches to modelling point patterns that comprise both deterministic and stochastic influences. This will involve work covering statistical theory, methodology, computation and application of cutting-edge statistical techniques for spatial data. The ideal candidate will have an excellent Honours/Masters degree in statistics (or equivalent), with an aptitude for research and strong computational skills (e.g. the R language). An interest in spatial applications is also highly desirable.

 

To express interest and learn more about the specifics of the project as well as the members of the supervisory team, visit the link above and get in touch.

 

About Dunedin:

Dunedin is a vibrant university town in the South Island of New Zealand, and home to the University of Otago — New Zealand’s oldest university. The statistics group within the Department of Mathematics and Statistics is an energetic group of researchers with expertise in many different areas; including but not limited to Bayesian modelling; smoothing and nonparametric statistics; statistical applications in ecology, seismology and genetics; stochastic modelling; and spatial statistics. We have strong ties to collaborators in statistics and other disciplines both within and outside of the university.