AI-enabled Patient and Service Monitoring for Resilient Critical Care

The project

Autonomous systems are an increasing part of the infrastructure of daily life. As the range and importance of such systems increases as the underlying technology rapidly develops, the UKRI has funded a range of investigatory research “nodes” to address the trustworthiness of autonomous systems.

An important aspect of resilience is to provide assurance that AI and autonomous systems can and will achieve their goals despite the uncertainty and disruption encountered in real-world environments. This exciting PhD studentship opportunity will contribute to the Resilience Node’s research by exploring how AI models could be developed, assured and deployed in complex hospital settings in order to explore the system response to patient deterioration, and the resilience of AI used as part of a complex adaptive sociotechnical system like the inpatient side of an acute hospital.

The aim of the project is to improve the resilience of the healthcare service and help to reduce the number of avoidable adverse outcomes, even under conditions of operational uncertainty and change. The PhD student will have the unique opportunity to collaborate with a multidisciplinary team from the disciplines of Computer Science, Engineering, and Clinical Medicine, and with stakeholders ranging from developers and clinicians to regulators and end users. 

Candidates are invited to familiarize themselves with the aims of the Resilience node. 

The project is led by the University of York’s Department of Computer Science, and the Principal Investigator for the Resilience Node is Professor Radu Calinescu.

Research supervision

The successful candidate will conduct their research under the supervision of Professor Radu Calinescu and Professor Ibrahim Habli in the Department of Computer Science; and Dr Tom Lawton, Consultant Critical Care & Anaesthesia and Head of Clinical Artificial Intelligence at Bradford Teaching Hospitals NHS Foundation Trust, and Honorary Visiting Professor in the Computer Science at the University of York.

Funding requirements

We are seeking a highly motivated candidate who should have, or expects to be awarded, a first-class or 2.1 degree or a master’s degree in Computer Science or any other relevant discipline. Preferred skills include writing, communication, presentation and organization skills. The studentship is open to UK and international students.

Apply for this studentship

To be considered, you must apply online for a full-time, on-campus PhD in Computer Science at the University of York. 

You must quote the project title ‘AI-enabled Patient and Service Monitoring for Resilient Critical Care’ in your application.

Please include the following documents in your application:

• A short research proposal (maximum 1,500 words) aligned with the topic of the PhD project.
• A statement of purpose explaining how your competencies and previous experiences makes you an appropriate candidate for this position.

Read more about research degrees in the Department of Computer Science at the University of York.

Deadlines

We will continue to accept applications until the studentship is awarded to a qualified candidate.

Interviews are expected to take place within approximately 14 days after the receipt of shortlisted applications.

The studentship will begin in April 2023 or September 2023.

Informal enquiries

Project enquiries: Professor Radu Calinescu (radu.calinescu@york.ac.uk) or Professor Ibrahim Habli (ibrahim.habli@york.ac.uk)

Application enquiries: cs-pgr-admissions@york.ac.uk