Scholarship details
Application dates
- Applications close
- 31 May 2024
What you'll receive
- You'll receive a stipend scholarship of $33,637 per annum for a maximum duration of 3.5 years. The duration includes an extension of up to 6 months (PhD) if approved for your candidature. This is the full-time, tax-free rate which will index annually.
- You will receive tuition fee coverage, either through a Research Training Program Fee-Offset place, or a QUT tuition fee sponsorship, for your research degree.
- As the scholarship recipient, you will have the opportunity to work with a team of leading researchers, to undertake your own innovative research in and across the field.
Eligibility
You need to meet the entry requirements for a QUT Doctor of Philosophy, including any English language requirements.
We are seeking to recruit a student to take up the scholarship and begin full-time study in July 2024.
You should have:
- a background in a relevant humanities and social science discipline, such as communication and media studies, STS or information studies, digital sociology, or internet studies
- recently completed a first-class honours degree, a research master degree, or a coursework master degree with a significant research component from a recognised institution and in a cognate discipline
- a strong interest in undertaking a three-year research project on an aspect of the Generative AI economy
- demonstrated excellent capacity and potential for research.
How to apply
Apply for this scholarship at the same time you apply for admission to a QUT Doctor of Philosophy.
- The first step is to email Distinguished Professor Jean Burgess detailing your academic and research background, your motivation to research in this field and interest in this scholarship and include your CV, full academic transcript and details of three referees (email and contact number) as soon as possible.
- Shortlisted applicants will be invited to an online interview with members of the supervisory team.
- If supported to apply, you will be invited to submit an expression of interest (EOI) following the advice at How to apply for a research degree.
- In your EOI, nominate Distinguished Professor Jean Burgess
as your proposed principal supervisor, and copy the link to this scholarship website into question 2 of the financial details section.
About the scholarship
The QUT Generative AI Lab (GenAI Lab) is a new, specialist research initiative focused on addressing the emerging social and cultural challenges and possibilities of Generative AI. Staffed by a multidisciplinary team led by Distinguished Professor Jean Burgess, the Lab aims to develop, disseminate and apply new sociotechnical research capabilities specific to Generative AI, combining critical, technical, and externally-engaged approaches. The GenAI Lab is aligned with QUT’s Digital Media Research Centre (DMRC) and the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S).
This scholarship supports one of a cohort of three PhD students who will commence together in the lab’s first year of operation.
The successful candidate will draw on theories from digital media and communication, sociology and/or STS to investigate an aspect of the Generative AI economy, understood as an emergent part of the platform economy. Topics might include: ownership, pricing and access to foundation models; the politics and cultures of GenAI development; innovation in the open source community; GenAI in the creative industries; the impact of GenAI on the business models of large platforms; new intermediaries in the GenAI economy; and generative advertising. Approaches might include critical data studies, political economy, ethnography, platform studies, and digital methods.
The candidate will be supervised by Distinguished Professor Jean Burgess and Dr Kevin Witzenberger and have the opportunity to engage in a dynamic environment with members of the QUT School of Communication and Digital Media Research Centre, as well as the national ADM+S Centre. The closing date for applications is 31 May 2024.