At a glance

Available to: 
Future Student
Level of study: 
Postgraduate Research
Citizenship: 
Australian citizens, Australian Permanent Residents and NZ citizens
International student

Seeking applicants with a degree in statistics, engineering, computer science, mathematics or physics, with relevant research experience.

Award value:
$27,082 per annum (2018 rate), indexed annually with an additional $14,150 per annum top up.
Applications open: 
1 June 2018
Applications close: 
22 July 2018
  • Eligibility

    Ideally, a competitive candidate will satisfy most, if not all, of the following criteria.

    1. A MPhil/MSc/BSc degree with a significant computational statistics and/or machine learning component.
    2. Proficient in linear algebra and multivariable calculus.
    3. Proficient in a programming language, such as MATLAB and/or Python.
    4. Prior experience working as part of data-driven projects.
    5. Research outputs such as publications, technical reports, or software package.
    6. Familiarity with or willingness to learn supervised, semi-supervised, and unsupervised machine learning methods.
    7. Familiarity with or willingness to learn computational statistics methods such as MCMC or variational inference.
    8. Good communication skills and fluency in spoken and written English.

    To be eligible you must:

    • be nominated by an enrolling school or institute at UQ;
    • be assessed by the Graduate School as meeting all conditions for admission into the PhD program;
    • not already hold a PhD;
    • not already be receiving a living allowance award, scholarship or salary providing a benefit greater than 75% of the RTP Scholarship living allowance rate to undertake the PhD;

    Students applying for this scholarship should plan to commence in October (Research Quarter 4), 2018.

    For more information about the project, please contact Dr Fred Roosta-Khorasani at fred.roosta@uq.edu.au.

    For more information about the entry requirements for Higher Degrees by Research at UQ, please visit the Graduate School's website.