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Modelling local population dynamics for whale sharks in the Maldives

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Data for this project will be provided by the Maldives Whale Shark Research Programme. The broad aim is to further the understanding of the local population dynamics of this enigmatic species.
Potential areas for investigation include:
• Robust stopover models for long-term mark-recapture data. The extension of these models to include biologically realistic behaviour (temporary migration, heterogeneous captures, individual covariates, environmental covariates). Robust estimation of recruitment probabilities and stopover duration on different temporal scales.
• Daily estimation of abundance and/or animal density. Modelling seasonal variation caused by, for example, lunar cycles, monsoon season, time-varying environmental conditions.
• Modelling animal movement and identifying habitual behaviour patterns. Investigating differences in behaviour for sharks of different ages or regions.
• The integration of different sampling methods including emerging technologies (drone surveys, sonar, eDNA). The inclusion of citizen science data.
• The potential extension of existing mark-recapture methods to a continuous-time framework.

Funding Notes

Multiple sources of scholarship funding are potentially available, including university, research council (EPSRC) and research group. Some are open to international students, some to EU and some UK only.

Applicants should have a good first degree in mathematics, statistics or another discipline (e.g., biology, computer science), with substantial statistical component. A masters-level degree is an advantage.

Further details of the application procedure, including contact details for the Postgraduate Officer, are available at View Website

How good is research at University of St Andrews in Mathematical Sciences?

FTE Category A staff submitted: 30.60

Research output data provided by the Research Excellence Framework (REF)

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