Log in

Research Fellow/Senior Research Fellow, Australian Centre for Health Services Innovation (QUT)

  • 12 Jan 2022 12:40 PM
    Message # 12256296
    Nicole White (Administrator)

    Research Fellow/Senior Research Fellow (Quantitative), Australian Centre for Health Services Innovation (AusHSI), Faculty of Health, Queensland University of Technology

    Opening Date: 6 January 2022

    Closing Date: 10 February 2022

    Status: Fixed-term, full-time basis for three (3) years

    About the Position

    The successful candidates will have the opportunity to work on a suite of research projects focusing on innovation and evaluation within health services, often in collaboration with health service partners. AusHSI conducts research into the organisation, funding and delivery of health services, with an emphasis on cost-effectiveness analysis and implementation science. The goal is to improve value for money among health services. Our broad research platforms include value-based healthcare, healthcare statistics and implementation science/knowledge translation.

    The successful candidates will work in high-functioning teams conducting health services research in priority fields including (but not limited to): clinical informatics and digital health; low value and high value care; health service & system reform; allied health models of care; respiratory health; cardiovascular health; vulnerable and complex populations; orthopaedics and trauma; mental health.

    There will be opportunity for the appointees to develop new projects and obtain competitive funding, in alignment with the objectives of the Centre and with the approval of the AusHSI leadership team.

    We are seeking 2-3 candidates, with a combination of quantitative research skills and experience, including health economics, statistics, data analytics and modelling, and research ideally undertaken in a healthcare setting. Experience in mixed methods research and working in multidisciplinary teams will be highly regarded.

    Whilst a clinical background and research experience in the health sector is an advantage, it is not essential, and we encourage statisticians with transferable skills, such simulation/agent-based modelling, to apply.

    The ideal candidate will have very strong academic writing skills, demonstrated through peer reviewed publications and/or other published work.

    For further information please visit

Powered by Wild Apricot Membership Software