Using AI to determine the mental health of an athlete (even before they realise it)

Masters by Coursework Scholarship

  • $10,000 pa (tax free*)
  • $5,000 training allowance
  • May be eligible for additional allowances totalling up to $3,000/year to support diversity and including (e.g. to help support people with caring responsibilities, living with a disability, from rural/remote areas or cultural considerations)

The Project:

Mental wellbeing is a huge factor in athlete performance. When an individual is under mental and physical pressure, depression, anxiety and mental stress are very prominent.

The phenotype and genetics of an individual can provide insights into an individual’s current and future mental health risk.

This project will use advanced AI phenotype profiling, genetics and face and voice analysis against standard mental health metrics to determine how accurately an individual’s mental health can be predicted through the season. Knowing the earliest signs, imperceptible to the athlete, and putting interventions in place to support them could mean the difference between finishing on the podium and not even making the trials due to mental illness.

The benefits and implications of the findings of this project extend well beyond athlete performance and into the general population.

This Masters project will be in collaboration with Precision Health Alliance/PHA in conjunction with QUT School of Biomedical Sciences, through a CSIRO-funded Next Generation Graduate Program (NGGP) grant, details are below. Principal supervisor – Prof Divya Mehta, QUT, lab website – .

When submitting the EOI, please mention the above project title and Principal supervisor name.

EOI form:

*See ATO for tax exempt income