PhD scholarships - Thrive: Finish School Well Program

Join us at The Human Technology Institute (HTI) at the University of Technology Sydney (UTS) to develop next-generation large Language model tools that can scale qualitative data analysis and help tackle social disadvantage in New South Wales. We are offering a highly competitive PhD scholarship to join our interdisciplinary research team at the Thrive: Finishing School Well Program . You will design, develop, and evaluate novel LLM-based pipelines for thematic analysis and summarisation of qualitative data, transforming these outputs into structured priors for Bayesian modelling. This approach will enable richer integration of qualitative insights into quantitative frameworks, supporting better education and policy decisions. About the Project Thrive: Finishing School Well is a research-in-action initiative bringing together world-leading researchers and experts in machine learning, digital technology, social science, and education. Thrive is uncovering what young people of all backgrounds need to finish high school well and thrive beyond it. By integrating cutting-edge digital technologies and machine learning with human-centered research, Thrive is setting a new standard for how social challenges are understood and addressed. You will collaborate with leading researchers in data science (UTS), social sciences (Western Sydney University) to develop statistical machine learning solutions for social good. This 3.5-year project will tackle educational disadvantage using data-driven methods, building new cross-disciplinary expertise in socio-technical systems and advancing innovative approaches to some of the most complex challenges in education. As a PhD candidate, you will join Thrive’s Next Generation AI Graduate Program student cohort. This program includes: A 6-month industry placement for real-world experience. A generous stipend and allowances for training and travel. Key Research Aims Develop LLM-driven pipelines for machine-assisted thematic coding, summarisation, and synthesis of large qualitative datasets. Assess the accuracy, validity, and interpretability of AI-generated outputs compared to human-led methods. Create methods for translating qualitative summaries into structured priors for Bayesian statistical models. Apply and evaluate these methods in an educational policy research context. Scholarship Offering $41,650 per annum (tax exempt) living stipend for 3.5 years $5,000 training allowance per annum for 3 years $5,000 travel allowance $840 thesis allowance Eligibility Australian citizen or permanent resident. Full-time enrolment at UTS. Must meet UTS PhD entry requirements (further information can be found here). Qualifications Master’s degree or First Class Honours in Mathematics, Statistics, Computer Science, Computer Engineering, or related fields such as Physics, Engineering, or Robotics, with strong mathematical, modelling, or machine learning skills Strong foundation in mathematics and comprehensive knowledge of principles Excellent written and verbal communication skills Ability to work effectively in a team and collaborate with others Good organizational and time management skills Analytical and critical thinking skills Proficient in programming languages such as MATLAB, Python, or R Prior research experience or publication record is desirable How to apply Send the following to Danet Chapman, Program Manager, at uts.edu.au: CV Academic transcripts Personal Statement outlining your motivation and interest in Thrive. Please note, only applications sent to the above email address will be accepted.

Location: Sydney, New South Wales, AU

Posted Date: 9/16/2025