Predictive models of oyster food safety

Developing a predictive model of food safety in oyster growing areas, integrating AI methods with high resolution sensor data

Degree type


Closing date

25 September 2023



Citizenship requirement

Domestic / International

About the research project

Many oyster growing areas are in estuaries. Estuaries are complex environments with riverine inputs, land run-off and tidal movement. The Tasmanian oyster industry has installed 60 sensors around the state, measuring salinity, temperature and tide height in real-time. This data set is supplemented with real-time/daily rainfall and river flow measurements from external sources, and targeted microbial samples of faecal coliforms levels to estimate public health risk. The complexity of the data set lends itself to artificial intelligence (AI) investigation to examine the effects of differing rainfall, tidal and riverine inputs and differing pollution sources. The selection of appropriate AI method is a challenge because of the uncertainty in measuring the accuracy of predictions. Also, it is critical to provide a high level of justification of the AI predictions that will be compared to traditional methods used for regulatory purposes.  This project will:

  • Investigate the artificial intelligence methodologies for the quantification of spatio-temporal relationships between water quality and various environmental drivers within oyster cultivation areas to support public health risk management of oyster farms.
  • Create quantitative models describing the environmental factors that drive faecal coliform levels in specified oyster leases.
  • Determine a methodology for quantifying sensitivity of individual leases to adverse water quality based on local environmental conditions.
  • Determine the role salinity plays in thermotolerant coliform concentration across different growing regions.
  • Examine whether regional predictions can provide value to maximising oyster production.
  • Develop an AI system capable of not only making accurate predictions but also providing an underpinning explanation based on environmental drivers.

A potential extension is to model oyster production in specific areas where data exists for drivers such as phytoplankton (chlorophyll A) data.

Primary Supervisor

Meet Dr Alison Turnbull


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 $31,500 per annum (2023 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.

Other funding opportunities and fees

For further information regarding other scholarships on offer, and the various fees of undertaking a research degree, please visit our Scholarships and fees on research degrees page.


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

Ensure your eligibility for the scholarship round by referring to our Key Dates.

Additional eligibility criteria specific to this project/scholarship:

  • Applications are open to Domestic/ International/ Onshore applicants
  • English language score must be above minimum entry requirements for this project
  • 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:

  • The applicant will need to be competent in computing and mathematics

Additional desirable selection criteria specific to this project:

  • Experience with artificial intelligence analyses will be an advantage

Application process

  1. Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
  2. Contact Dr Alison Turnbull to discuss your suitability and the project's requirements; and
  3. In your application:
    • 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.
    • Submit a signed supervisory support form, a CV including contact details of 2 referees and your project research proposal.
  4. Apply prior to 25 September 2023.

Full details of the application process can be found under the 'How to apply' section of the Research Degrees website.

Following the 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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