PhD Studentship: Trustworthy Autonomous Systems in Health (TASH)

As advances are made in Artificial Intelligence (AI), the technology is being applied to health-related problems. How do we evaluate the trustworthiness of these systems in the health context? This project will push the boundaries of our understanding of trustworthy autonomous systems in health through a mix of computer science and sociotechnical research, driven by the implementation of a real system. The project will develop and expand an existing autonomous system for early detection of deteriorating health in hospital patients, using safety, reliability and acceptability of a machine learning clinical deterioration score (CARDS) in comparison to the existing extensively used basic Early Warning Score (NEWS2).  Using this system, and existing trustworthy autonomous frameworks, the project will first develop a further understanding of the healthcare ecosystem into which the system will be deployed along with the practical, professional and societal hurdles to its implementation. The project will then identify variations and extensions required by medical autonomous trustworthy systems leading to the development of a framework for trustworthy systems, focused on the specific needs of the health ecosystem, including organizational requirements, clinical interactions, user interfaces and regulatory bodies, etc.

Working within the Southampton Biomedical Research Centre, the project sits within a world-leading digital ecosystem centred around translating cutting-edge tools and technologies to improve patient outcomes. The University of Southampton boasts a nationally leading compute cluster. The University Hospital Southampton is recognised as a global digital exemplar. The project will implement and test AI techniques including what trustworthiness means, on rich, real-world patient data. The CARDS algorithm itself has been developed by collaborators in the University of Cambridge who will also be supporting this work. 

If you wish to discuss any details of the project informally, please contact Professor Adriane Chapman, Digital Health and Biomedical Engineering Research Group, Email: Adriane.Chapman@soton.ac.uk Web page: https://www.southampton.ac.uk/people/5xhdw9/professor-age-chapman

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honour degree, or its international equivalent) in one of the following related subject areas:

• Computer Science
• Data and Information Science
• Digital Health
• Artificial Intelligence / Machine Learning
• Bioengineering (or Biomedical Engineering)

Closing date: applications should be received no later than 31 August 2023 for standard admissions, but later applications may be considered depending on the funds remaining in place. Please apply once you are ready and do not leave your application to the last minute because the funding allocation takes place every couple of months.

Funding: For UK students, Tuition Fees and a stipend of £17,668 tax-free per annum for up to 3.5 years.

Applications should include:

Research Proposal outlining how you would undertake the project

Curriculum Vitae

Two reference letters

Degree Transcripts/Certificates to date

For further information please contact: feps-pgr-apply@soton.ac.uk

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