PhD Scholarship – in Robust Bayesian methods for Expert Judgement and Uncertainty (Adelaide)

EOI: Closing 30 September

A fully funded PhD project at Adelaide University.

BayesGRADE: A Robust Bayesian Framework for Quantifying Expert Judgement and Uncertainty in Evidence-Sparse Clinical Guidelines

Clinical practice guidelines are usually built on strong trial evidence. But for rare diseases, emerging technologies, and other novel decision problems, such evidence is often scarce or absent, leaving clinicians and guideline panels reliant on expert judgement. GRADE, the world’s leading framework for rating certainty in medical evidence, was designed for data-rich settings and offers little guidance for developing recommendations without empirical research, leading to simplistic approaches for collecting ‘expert evidence’ that are subject to expert biases and can produce spurious recommendations. This project will develop new Bayesian methods, including a structured protocol for capturing expert judgement more reliably, that formally represent each expert’s reliability and let that uncertainty flow into a guideline’s certainty rating and recommendation strength, improving recommendations for underserved patients, including rare diseases, when evidence is thin or missing.

Project SRTSR0182.

Expressions of Interest close on 30th Sept 2026.

For any queries/further information email: Dr. Chaitanya Joshi: chaitanya.joshi@adelaide.edu.au