Scholarship details

Study levels

Postgraduate and Research

Student type

Future students

Study area

Science, technology and engineering and mathematics


Australian only

Application dates

Applications close
28 February 2021

What you'll receive

  • The successful applicant will receive a living allowance valued at AU$30,000 per annum for three years.
  • The scholarship is for full time study and can be used to support living costs.
  • Includes provision for the additional 12 weeks paid sick leave and paid maternity leave.


You must:

QUT and the Centre for Data Science are committed to equity and diversity among our staff and students, to ensure that we mirror the diversity of the community in which QUT exists. In 2018, this was recognised by QUT receiving a Bronze Award in the inaugural SAGE Athena SWAN gender and diversity program.

Woman and Aboriginal and Torres Strait Islander students are encouraged to apply.

The provision of a scholarship is conditional on successful application and admission to the IF49 Doctor of Philosophy course. Eligibility for admission to a research degree is determined by the Graduate Research Centre.

How to apply

Please submit your application via QUT's Application Portal:

  1. Follow the how to apply steps.
  2. You must submit your expression of interest by 28 February 2021.
  3. Indicate your interest in this scholarship by nominating Distinguished Professor Kerrie Mengersen as principal supervisor and include the name of this scholarship in the financial details section.
  4. As part of the EOI process applicants must provide their CV, full academic transcripts, English language results (if required), and proof of citizenship. In addition to the required documentation, please include the following in your EOI:
  • a cover letter
  • a summary (up to two pages) of your career outlining your experience in data science practice or research)
  • contact details of three referees (full name, email, and phone number).
  1. If your EOI is accepted you will be invited to submit a full application including a research proposal to finalise your application.

What happens next?

Applications will close no later than 15 March 2021.


The conditions for retaining the scholarship are set out in the rules of the QUT Postgraduate Research Award (Domestic). Excluding the provision for extension.

About the scholarship

The Australian Bureau of Statistics and QUT Centre for Data Science are partners in a world leading program of research in data science in the government statistics domain and in the priority areas of agriculture and geospatial statistics. The Australian Bureau of Statistics is Australia’s national statistical agency providing trusted official statistics on a wide range of economic, social, population and environmental matters. The QUT Centre for Data Science’s vision is to be a national and global leader in the development of frontier methods for the use of data to benefit our world.

What’s in it for you?

  • Opportunity to work closely with the Australian Bureau of Statistics.
  • Opportunity to work with leading researchers in data science.
  • Access to large datasets.
  • Access to a community of like-minded data science researchers and practitioners.

Research projects

Applicants will be invited to apply for one of the following projects:

  1. Optimisation of work processes focusing on automating area design. This includes the development of a set of processes to efficiently update the Australian Statistical Geography Standard (ASGS). Supervisor: Distinguished Professor Kerrie Mengersen.
  2. Optimisation of work processes focusing on identifying labour markets and functional areas. This includes the development of a model or algorithm to identify labour markets and functional areas to support design of the Australian Statistical Geography Standard (ASGS). Supervisor: Distinguished Professor Kerrie Mengersen.
  3. Statistics from combined sources using agriculture case studies. This includes the development of a production process to combine survey data with alternative data sources using deep neural nets, delivering small area outputs and enabling a transition from survey data to administrative inputs. Supervisor: Distinguished Professor Kerrie Mengersen.

For further information, please contact:

Distinguished Professor Kerrie Mengersen

Director, QUT Centre for Data Science


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