Stochastic Models for Conservation

Stochastic Models for the Conservation of Endangered Species

Degree type

PhD

Closing date

18 July 2022

Campus

Hobart

Citizenship requirement

Domestic/International

About the research project

In populations of endangered species, management strategies referred to as genetic rescue have been advocated in order to help avoid extinction. An example of considerable concern in the Australian context is the conservation management of Tasmanian Devils suffering from the Devil Facial Tumour Disease (DFTD), which puts them in danger of extinction. Conservation strategies have been used with the hope of increasing the genetic diversity of the wild population, but this remains a challenging problem. An important factor in this context is the ability to assess the impact of conservation efforts.

This project will focus on developing models for the numerical assessment of conservation strategies, and is an exciting opportunity to help make a difference. We aim to develop of a suite of algorithmic techniques and make the code publicly available to the research community.

You will work on simulation and/or theoretical models using statistical analysis of real data. You will have an opportunity to be part of a rich collaborative environment and interact with mathematicians and biologists studying the wild populations of Tasmanian Devils.

Primary Supervisor

Meet Prof Barbara Holland

Funding

Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

  • a living allowance stipend of $28,854 per annum (2022 rate, indexed annually) for 3.5 years
  • a relocation allowance of up to $2,000
  • a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.

Eligibility

Applicants should review the Higher Degree by Research minimum entry requirements.

Additional eligibility criteria specific to this project/scholarship:

Applicants must be able to undertake the project on-campus

Selection Criteria

The project is competitively assessed and awarded.  Selection is based on academic merit and suitability to the project as determined by the College.

Additional essential selection criteria specific to this project:

  • Applicants must already have been awarded a first class Honours degree or hold equivalent qualifications or relevant and substantial research experience in an appropriate sector
  • Applicants must be able to demonstrate strong research and analytical skills.
  • Knowledge and skills in applied probability, probabilistic operations research, statistics or related area is required.
  • Knowledge and skills in simulation and coding or related area is required.

Additional desirable selection criteria specific to this project:

  • Degree-level undergraduate education in maths or a related subject.
  • Knowledge and skills in biological mathematics, evolutionary genetics or related area will be highly regarded.

Application process

There is a three-step application process:

  1. Select your project, and check you meet the eligibility and selection criteria;
  2. Contact the Primary Supervisor, Prof Barbara Holland to discuss your suitability and the project's requirements; and
  3. Submit an application by the closing date listed above.
    • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
    • As part of your application, you will be required to submit a covering letter, a CV including 2 x referees and your project research proposal.

Following the application closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.

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