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Evaluating clinical AI in real-time

This project is closed for international students.

Project summary

Program
PhD
Location
Herston
Research area
Information and computing sciences

Project description

The proposed research project is a component of the NASCENT Medical Research Future Fund project to develop and validate a research infrastructure that enables researchers at Australian hospitals to trial and evaluate AI-based clinical systems that provide diagnostic, treatment and prognostic support to clinicians. A key hurdle for implementing AI within Australian hospitals is a real-time trial using real patient data to ensure the AI is fit for clinical use. The proposed project will focus on research that helps to overcome this hurdle. In particular, the PhD student will support the evaluation of two use cases for predicting clinical deterioration and sepsis in hospital wards.  The evaluation trials will be conducted at multiple hospital sites around Australia with the objective of demonstrating suitability for implementation into clinical practice.

The student will have the opportunity of identifying the final scope of their research at the beginning of their candidature. During that phase, they will research current state-of-the-art methods for evaluating clinical AI in real-time environments and can propose a suitable research topic to tie in with the use-case evaluations over the life of their candidature. Examples of such topics could include real-time evaluation methods that incorporate clinical and patient feedback, drift monitoring and updating, automated and real-time AI improvement modelling or specific AI technique evaluation, such as clinical LLM use and evaluation.  In the second stage of the project the student will develop methods to use during the trials and in the final phase of the project the student will trial their methods and report on the findings.

Research environment

You will work out of our RBWH (Herston) campus and will have access to our large computing centre.

Scholarship

This is an Fellowship support scheme scholarship project that aligns with a recently awarded Australian Government grant.

The scholarship includes:

  • living stipend of $36,400 per annum tax free (2025 rate), indexed annually
  • your tuition fees covered
  • single overseas student health cover (OSHC).

Learn more about the Fellowship support scheme 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 python, data engineering and/or data science methods would be of benefit to someone working on this project.

You will demonstrate academic achievement in the field/s of computer science, data science, data engineering and the potential for scholastic success.

A background or knowledge of medical or clinical experience is highly desirable.

How to apply

This project requires candidates to commence no later than Research Quarter 4, 2025. To allow time for your application to be processed, we recommend applying no later than 30 June, 2025 30 March, 2024.

You can start in an earlier research quarter. See application dates.

Before you apply

  1. Check your eligibility for the Doctor of Philosophy (PhD).
  2. Prepare your documentation.
  3. Contact Professor Ian Scott (i.scott@uq.edu.au) to discuss your interest and suitability.

When you apply

You apply for this scholarship when you submit an application for a PhD. You don’t need to submit a separate scholarship application.

In your application ensure that under the ‘Scholarships and collaborative study’ section you select:

  • My higher degree is not collaborative
  • I am applying for, or have been awarded a scholarship or sponsorship
  • UQ Earmarked Scholarship type.

Apply now

This project is not available to international students