Closed-loop model predictive control for hypercapnic respiratory failure patients
Eligible for funding* | PhD
Currently, due to a struggling healthcare system, patients with hypercapnic respiratory failure are only seen by clinicians once an hour, meaning their oxygen control is suboptimal.
Your work will include:
- Building advanced mathematical models of cardiovascular, respiratory, and autonomic systems
- Personalising these models for individual patients in emergency care
- Using them to predict blood gas concentrations and optimise oxygen delivery (FiO₂) in real time
This is a unique opportunity to bridge theory and practice, combining computational modelling, control engineering, and clinical implementation to improve patient outcomes and ease pressure on failing healthcare systems. If you’re ready to apply your skills to a project that could change emergency care, we’d love to hear from you!
Desired skills
Ideal candidates will have:
- A background in mathematical modelling
- Experience and/or interest in learning control systems and embedded implementation
- A desire to see their work make a real difference in clinical settings
Contact and supervisors
For more information or to apply for this project, please follow the link to the supervisors below:
Contact/Main supervisor
Supporting Supervisors
- Merryn Tawhai
- Geoff Chase
- Ella Guy
Eligible for funding*
This project is eligible for funding but is subject to eligibility criteria & funding availability.
Page expires: 8 June 2026