Faculty/School

Faculty of Science

School of Mathematical Sciences

Topic status

We're looking for students to study this topic.

Research centre

Centre for Data Science

Primary Supervisor

Professor Chris Drovandi
Position
Professor
Division / Faculty
Faculty of Science

Overview

Bayesian statistics provide a framework for a statistical inference for quantifying the uncertainty of unknowns based on information pre and post data collection.

This information is captured in the posterior distribution, which is a probability distribution over the space of unknowns given the observed data.

The ability to make inferences based on the posterior essentially amounts to efficiently simulating from the posterior distribution, which can generally not be done perfectly in practice.

This task of sampling may be challenging for various reasons:

  • The posterior distribution is irregular (e.g. multi-modal, non-normal and/or complex dependency structures between components).
  • The likelihood function (the probability function of the data given unknowns) of the statistical model of interest may be expensive to compute.
  • The likelihood function is intractable but can be estimated unbiasedly.
  • The likelihood function is completely intractable but simulation from the model is feasible.
  • The model involves a hierarchy of several levels and has a large number of parameters.
  • There are several competing models of interest.

Research engagement

Reading relevent literature,  implementation of advanced methods

Research activities

The student will develop or apply computational methods for Bayesian statistics.  The student will work with Chris Drovandi, and potentially other collaborators.

Research skills

Advance skills in statistical inference, statistical computing, data science, programming

Outcomes

Make some progress towards a new idea or apply advanced methods to a real problem.

Skills and experience

Ideally the candidate will have a strong interest in statistics and programming.  The project can be tailored to the candidates' experience.

Start date

2 November, 2026

End date

19 February, 2027

Location

Gardens Point.  Partially working from home is also possible.

Keywords

Contact

Chris Drovandi

31381756

c.drovandi@qut.edu.au