CSIRO Industry PhD Scholarship: AI-Based Detection and Catch Validation of Sharks in the Southern and Eastern Scalefish and Shark Fishery

Funding and duration

four year scholarship package totalling approximately $48,000 per annum tax exempt (2026 rate); four-year scholarship and research training program.

Project overview

Project title

AI-Based Detection and Catch Validation of Sharks in the Southern and Eastern Scalefish and Shark Fishery

Project description

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.

Supervisory team

University

Name of university supervisor | Alyssa Marshell

Name of university | University of Tasmania

Email address | alyssa.marshell@utas.edu.au

Faculty | IMAS

CSIRO

Name of CSIRO supervisor | Candice Untiedt

Email address | candice.untiedt@csiro.au

CSIRO Research Unit | Environment

Industry

Name of industry supervisor | Simon Boag

Name of organisation | Southern Shark Industry Alliance

Email address | simon@atlantisfcg.com

Further details

Primary location of student | CSIRO Hobart, Castray Esplanade, Battery Point TAS 7000, Australia

Industry engagement component location | Southern Shark Industry Alliance Inc, SEAMEC Bullock Island Road, Lakes Entrance VIC 3909, Australia Australian Fisheries Management Authority (AFMA) Level 3, 15 Lancaster Place, Majura Park ACT 2609, Australia

Other locations | University of Tasmania, 15-21 Nubeena Crescent, Taroona TAS 7053, Australia

Ideal student skillset | Essential: 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. Desirable: Experience working with large datasets, statistical modelling, or fisheries science is desirable but not essential.

Application close date | Open until position filled

Apply | UTAS