Predicting mental health status

Degree type


Closing date

27 March 2023



Citizenship requirement


About the research project

There is a significant body of work focusing on mental health in the workplace. This work has predominantly focused on students (at all levels), school teachers, emergency service professionals, health professionals and other high stress and personal service occupations. There is however very little literature addressing the growing impact of mental health issues in higher education academics and administrators. Given the nature of the work done by academics and administrators, the loss of a person due to mental health issues has the potential to impact hundreds of students and entire schools or departments. This project will take an informatics approach to collect data, and develop predictive models to identify those who are most at risk and identify the timelines and triggers to provide a mechanism for proactive mental health initiatives to be provided and ensure that an employee does not reach burn out or require prolonged medical intervention. This project has a focus on keeping the higher education sector healthy and productive.

Primary Supervisor

Meet Professor Anna Shillabeer


Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

  • a living allowance stipend of $31,500 per annum (2023 rate, indexed annually) 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)

If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.

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


Applicants should review the Higher Degree by Research minimum entry requirements.

Additional eligibility criteria specific to this project/scholarship:

  • Background in Computer Science and/or Data Science

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:

  • Practical experience and knowledge of statistics and statistical analysis

Additional desirable selection criteria specific to this project:

  • Practical experience and understanding of machine learning and/or data mining

Application process

There is a three-step application process:

  1. Select your project, and check you meet the eligibility and selection criteria;
  2. Contact the Primary Supervisor, Professor Anna Shillabeer to discuss your suitability and the project's requirements; and
  3. Submit an application by the closing date listed above.
    • 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.
    • As part of your application, you will be required to submit a covering letter, a CV including 2 x referees and your project research proposal.

Following the application 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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