Closed-loop model predictive control for hypercapnic respiratory failure patients

About the Project

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