Kristen Gibbons

Machine Learning in the Paediatric Intensive Care Unit: Development of Risk Prediction Models

Project Summary

This PhD project will develop interpretable machine learning models to support clinical decision-making for critically ill children in paediatric intensive care units (PICUs). Using high-resolution data from over 32,500 patient admissions across three international PICUs, the research will focus on early detection of patient deterioration. Emphasis will be placed on explainability and reasoning, ensuring that predictions and recommendations are transparent and clinically meaningful. The project will explore how to design and implement decision support tools that align with clinicians’ workflow and reasoning processes in high-pressure environments. The project aims to improve outcomes of Australia’s most critically unwell children by supported enhanced clinical decision making and, in turn, timely interventions, ultimately supporting precision medicine in critical care.

Research Environment

This PhD project is embedded within the Children’s Intensive Care Research Program (ChIRP), a world-leading research group dedicated to improving outcomes for critically ill children. ChIRP fosters a collaborative, multidisciplinary environment involving clinicians, computer scientists, data scientists, and international partners. The successful candidate will benefit from access to large-scale clinical datasets, close engagement with paediatric intensive care experts, and a strong culture of innovation, integrity, and compassion. With a focus on impact-driven research, students will be supported to translate findings into real-world clinical practice and contribute to global improvements in child health.

Before you apply

Before submitting an application you should:

1. check your eligibility for a Doctor of Philosophy (PhD)
2. prepare your documentation
3. contact Professor Kristen Gibbons (k.gibbons@uq.edu.au) to discuss your interest and suitability
4. To be considered for this PhD opportunity, please email the following documents to Professor Kristen Gibbons (k.gibbons@uq.edu.au):

• A cover letter outlining your interest in the project and explaining how you meet the selection criteria listed below
• A current CV
• Academic transcripts from all previous tertiary study
• Contact details for two academic or professional referees

Selection criteria

• A working knowledge of machine learning, clinical data analysis, and explainable artificial intelligence
• A background or knowledge of healthcare informatics, time-series data, or human-centered
• Evidence of research capability through thesis work and/or relevant technical or analytical experience
• Strong communication and interpersonal skills
• A demonstrated enthusiasm for working in multidisciplinary teams, including collaboration with clinical and industry partners
• The ability to work independently and remain motivated to deliver high-quality research outcomes

Please do not hesititate to get in touch with me to discuss more.