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Postdoctoral Fellow in spatial statistics (New Zealand)
jueves, 13 de febrero de 2020

Dear allstat members,

We announce a new postdoctoral position in spatial statistics, to join the Spatial Analysis Group Otago (SAGO) in the Dept. of Mathematics and Statistics, University of Otago, Dunedin, New Zealand.

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
Position duration: 2 years, full-time
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).
Closing date: 31st March 2020

We are currently seeking applications for a 2-year full-time postdoctoral fellowship, available as part of a prestigious Royal Society of New Zealand Marsden Fund Research Grant recently awarded. The postdoc 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".

Broadly, the research project deals with the challenging task of developing 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 determine whether a cluster of disease cases, for example, is likely explained by a single contaminating source or by contagion between infected individuals.

The successful applicant will be based primarily at the University of Otago, in the university town of Dunedin, in the beautiful South Island of New Zealand. They will work closely with the supervisory team to develop new and refine existing approaches to modelling point patterns that comprise both deterministic and stochastic elements. This will involve work covering statistical theory, methodology, computation and application of cutting-edge statistical techniques for spatial data. The successful candidate will gain substantial experience in academic research, bolstering their CV. Publication authorship and conference attendance will be primary objectives.

The ideal candidate will have, or be soon to be awarded, a Ph.D. degree in statistics (or equivalent), with an aptitude for research, strong computational skills (e.g. the R language) and an interest in spatial applications.

For more information on the position, Dunedin, and to apply, visit the link above. See also for information on our department and for the SAGO group. Informal enquiries can be directed to Dr. Tilman Davies; Esta dirección de correo electrónico está protegida contra los robots de spam, necesita tener Javascript activado para poder verla .