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Scalable Bayesian inference for secure and reliable decision making

Project summary

Program
PhD
Location
St Lucia
Research area
Mathematical sciences

Project description

Bayesian methods are central to modern statistical modelling and decision making, but current scalable algorithms are constrained to simple models or rely on strong approximations, limiting reliability for complex, and often more realistic, problems.

This project will develop scalable Bayesian algorithms that achieve accurate, privacy-aware inference for large datasets. You will explore continuous-time and gradient-driven approaches to expand the range of models amenable to principled Bayesian analysis, deliver theoretical insights, and produce open-source implementations with broad impact across statistics, machine learning, and data science.

Scholarship

This project is supported by the Research project scholarship.

This scholarship includes:

  • living stipend of $39,220 per annum tax free (2026 rate), indexed annually
  • tuition fees covered.

This scholarship includes:

  • living stipend of $39,220 per annum tax free (2026 rate), indexed annually
  • tuition fees covered.

Learn more about the Research project scholarship.

Supervisor

Preferred educational background

Your application will be assessed on a competitive basis.

We take into account your:

  • previous academic record
  • publication record
  • honours and awards
  • employment history.

A working knowledge of Bayesian inference, Monte Carlo methods, scientific computing and programming would be of benefit to someone working on this project.

You will demonstrate academic achievement in the fields of statistics, machine learning (or a closely related discipline), and the potential for scholastic success.

A background or knowledge of computational statistics, linear algebra, federated learning is highly desirable.

How to apply

You must submit an expression of interest (EOI) by 23 October, 2026 23 October, 2026.

Before you apply

  1. Check your eligibility for the Doctor of Philosophy (PhD).
  2. Prepare your documentation.
  3. If you have any questions about whether the project is suitable for your research interests, contact Dr Matthew Sutton (m.sutton2@uq.edu.au).

When you apply

To apply, submit an expression of interest (EOI) for the program. You don't need to apply separately for the project or scholarship. How to submit an EOI

In your EOI, complete the ‘Scholarship/Sponsorship’ section with the following details:

  1. Are you applying for an advertised project: 'Yes'
  2. Project: 'Research project scholarship'
  3. Scholarship Code Listed in the Advertisement: SCALABLE-SUTTON
  4. Link to Scholarship Advertisement: https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/scalable-bayesian-inference-secure-and-reliable-decision-making

Submit an EOI

Do you have questions?

The Graduate Research School is here to help.

Contact us