Machine vision for increasing safety in healthcare | UniSC | University of the Sunshine Coast, Queensland, Australia

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Machine vision for increasing safety in healthcare

PhD scholarship

Project summary

Healthcare systems are under increasing pressure due to rising demand, workforce shortages, and complex clinical environments. Advances in artificial intelligence and machine vision provide new opportunities to support clinical decision-making and improve the safety and efficiency of healthcare delivery.

We are seeking an enthusiastic and motivated person to join our research team working at the intersection of machine vision, health informatics, and clinical innovation as a Master’s of Science research student. The research project aims to design, develop, and evaluate machine vision–based tools to support safer, more efficient healthcare practices.The successful candidate will contribute to research developing computer vision models, dataset curation, clinical workflow analysis, and evaluation of AI enabled decision-support technologies to proof of concept in laboratory and implementation in healthcare environments.

This is an excellent opportunity for a student wanting to build applied expertise in digital health, AI, and translational research.

Applications close

15 May 2026 8:59am

To complete an application you will need to create an account and login to the HDR scholarships portal.

Summary of position 

The successful candidate will lead a project that may include some of the following:

  • Machine vision applications in clinical health environments
  • Human–AI interaction in healthcare settings
  • Integration of sensor and wearable data
  • Decision support and workflow optimisation
  • Development and validation of image based algorithms
  • Privacy preserving methods for health data
  • Implementation considerations for digital health technologies

There is an opportunity for the project scope to be refined to align with the student’s interests and background while remaining within the parameters of the lab and project requirements. 

You will join a supportive and collaborative research environment embedded in active digital health and ageing, and AI projects in the Health Productivity Lab at UniSC. You will have access to mentoring, clinical partners, and industry collaborators. You will publish peer reviewed research and develop skills in ethics, research methods, AI development, knowledge translation and digital health innovation.

Ideal eligible candidate

The ideal candidate will have a qualification in computer science, health science, biomedical engineering, data science, nursing, allied health, or related field

  • Domestic applicant - Australian or New Zealand citizen. Australian permanent resident.  
  • Ability to meet entry requirements for Master by Research at UniSC
  • Minimum of 3 years industry experience    
  • Demonstrated research capability (e.g., thesis, publications, or relevant experience)
  • Ability to work collaboratively in a research team
  • Demonstrate strong written and verbal communication skills.

Inclusions

The full-time candidature period is 1.5 years, with possibility of a 6-month extension. Coverage for the domestic HDR student includes:

Stipend - $45 000 (AUD) per annum, paid fortnightly and is tax-free for full-time students.Tuition fees - Full coverage, with a value of $29 300 per annum.Relocation allowance - Up to $2,000 to relocate to a UniSC campus

All inclusions are in accordance with UniSC Research scholarship guidelines.

Considering a PhD or Masters by Research?

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