AI-based detection and catch validation of sharks in the Southern and Eastern Scalefish and Shark Fishery.

About the research project

This project will develop artificial intelligence (AI) computer vision models to automatically detect, measure, and validate shark catches in the Gillnet, Hook and Trap sector of the Southern and Eastern Scalefish and Shark Fishery (SESSF). The research will focus on gummy shark (Mustelus antarcticus) and school shark (Galeorhinus galeus), with additional work on sawshark and elephant fish as key byproduct species.

Using electronic monitoring (EM) video, the project will develop models to detect sharks, estimate length, determine sex and condition, and generate species-specific length-frequency distributions. These will be converted to whole weight estimates and validated against processed catch weights recorded at offloading.

The project addresses a key challenge emerging in the fishery as shark fishing vessels request transition toward on-board processing. At-sea processing and freezing landed product of a higher quality reduces transiting times to/from grounds and reduces onshore processing costs. However, traditional EM and observer monitoring approaches struggle to verify catch composition and volume, which is especially important if skin off fillets are landed rather than a shark body.

The outcome will be operational AI tools to support fisheries management, compliance, and sustainable harvest in collaboration with industry, AFMA, CSIRO, and the University of Tasmania.

Primary supervisor

Meet Doctor Alyssa Marshell

Funding

The successful applicant will receive a scholarship which provides:

• a living allowance stipend funded by CSIRO Industry PhD Program and Southern Shark Industry Alliance Inc of $36,071 per annum 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)

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

Additional Funding

If successful, applicants will also receive a CSIRO Industry PhD Program and Industry (Southern Shark Industry Alliance Inc) top-up scholarship of $12,000 per annum for 3.5 years. This scholarship is funded from Southern Shark Industry Alliance Inc.

Other funding opportunities and fees

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

Eligibility

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:

The student must:

a)     Be an Australian citizen or Permanent Resident, or a New Zealand citizen. 

b)     Meet participating university PhD admission requirements.

c)     Meet university English language requirements.

d)     Not have previously completed a PhD.

e)     Be able to commence the Program in the year of the offer.

f)      Enrol as a full-time PhD student. Part-time arrangements may be considered if approved by the supervisory team and in accordance with university policy.

g)     Be prepared to be located at the project location(s) that the host university has approved and, if required, comply with the host university’s external enrolment procedures.

h)     Be prepared to undergo onboarding to CSIRO, which will include passing mandatory government background checks (allow for between 4 to 8 weeks) and complete any other CSIRO requirements. 

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:

• A background in computer science, data science, or a related quantitative discipline.
• Programming (preferably Python or R), experience with data analysis, and machine learning or computer vision.
• Strong analytical skills.
• Familiarity with deep learning frameworks (e.g. PyTorch or TensorFlow), image processing or ecological data analysis. 
• An ability to work collaboratively across research and industry partners.
• An interest in applying advanced technologies to real-world environmental and fisheries management challenges.  

Additional desirable selection criteria specific to this project:

• Experience working with large datasets, statistical modelling, or fisheries science is desirable but not essential.  

Application process

1. Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
2. Contact Doctor Alyssa Marshell 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 1 October 2026.

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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