Melanoma Early Detection - 3 PhD positions available

Project opportunity

This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.

Skin cancers, including melanoma, present a significant health, social and economic burden in Australia. Despite the rising incidence of melanoma, the most deadly form of skin cancer, there is currently no national or population-based screening program available.

PhD scholarships are available for exceptional students to complete a PhD as part of a National Health and Medical Research Council Centre of Research Excellence (CRE) in Skin Imaging and Precision Diagnosis. The aim of this CRE is to identify how innovative 3D total-body imaging technologies can be integrated into the healthcare pathway to improve melanoma early detection, and ultimately reduce the health and economic burden caused by melanoma skin cancer.

We have three full-time PhD opportunities available focusing on melanoma early detection in the following areas: artificial intelligence, statistics and public health.

PhD student 1 and 2 will focus on the novel field of dermatology image analysis and biostatistics, and each derive their own program of research in this area. This will include developing and implementing artificial intelligence (AI) algorithms based on convolutional neural networks (CNNs) that support clinicians in their decision making to improve the accuracy of melanoma early diagnosis. These projects will investigate and evaluate the impact of integrating explainable AI algorithms into clinical workflows. A high knowledge of AI systems, neural networks, computer science and statistics would be of benefit to someone working on this project. 

A third PhD student opportunity is available in the field of public health assessing the use of consumer technologies for melanoma screening. The objective of this PhD is to improve confidence, willingness and trust of people to engage in melanoma skin self-examination practices. The PhD student will work with consumers to systematically derive educational materials for melanoma early detection to facilitate uptake of skin self-examination.

These projects use data from the Australian Centre of Excellence for Melanoma Imaging and Diagnsois (ACEMID), a longitudinal cohort study collecting 3D imaging data from 15,000 participants across Queensland, New South Wales and Victoria.

The successful applicants will work as part of the CHSR and Dermatology Research Centre teams at UQ, as well as collaborate with researchers from the University of Sydney and Monash University. Our large multi-disciplinary team includes dermatologists, behavioural psychologists, health economists, epidemiologists, and AI, computer and data scientists who are working together to improve melanoma early detection in Australia.

Scholarship value

As a scholarship recipient, you'll receive: 

  • living stipend of $28,854 per annum tax free (2022 rate), indexed annually
  • tuition fees covered
  • single Overseas Student Health Cover (OSHC)

Supervisor

Professor Monika Janda

For more information on this project, please contact Danielle Mills at d.mills@uq.edu.au.

Preferred educational background

Your application will be assessed on a competitive basis.

We take into account your

  • previous academic record
  • publication record
  • honours and awards
  • employment history.

The applicant/s will demonstrate academic achievement in either the field/s of public health, statistics or artificial intelligence and the potential for scholastic success.

Latest commencement date

If you are the successful candidate, you must commence by Research Quarter 4, 2024. You should apply at least 3 months prior to the research quarter commencement date.

If you are an international applicant, you may need to apply much earlier for visa requirements.

How to apply

You apply for this project as part of your PhD program application.

View application process