PhD Studentship in Biomedical Engineering

Project title: Remote Monitoring in Urology Using AI

Supervisors:  

• Professor William Holderbaum, email: w.holderbaum@reading.ac.uk
• Dr Christopher Blick email: Christopher.Blick@royalberkshire.nhs.uk

Project Overview: The growth of AI in the healthcare sector is delivering real world change and promises to transform the future of medicine. The project introduces a novel approach to managing common urological scenarios by integrating remote monitoring systems with AI and machine learning to predict clinical outcomes. Urinary tract infections lead to 150,000 hospitalisations in the UK each year costing the NHS an estimated £380 million annually. The innovative aspects of this research lie in its use of AI-driven predictive models that analyse real-time data from IoT-enabled devices to forecast patient outcomes, such as the risk of sepsis from urinary tract infections. This proactive approach enables timely interventions, significantly reducing emergency hospital admissions and improving patient care in community and secondary care settings.

The PhD researcher will develop a comprehensive remote monitoring system, capable of continuous tracking of clinical variables like urination frequency and bladder volumes, which represents a major advancement in patient management.

This project offers the student a comprehensive training experience that spans both technical and interdisciplinary domains. Training and Experimental Work: The student will gain hands-on experience in cutting-edge AI and machine learning techniques, with a focus on developing and applying predictive models to real-time data from IoT-enabled devices. This experience will provide expertise that will be transferable across a broad scope of health tech and healthcare settings. The student will be fully involved across all aspects of the project, from data acquisition and analysis to the development and implementation of AI-driven remote monitoring systems. Additionally, the student will have the opportunity to work closely with clinical data, enhancing their understanding of medical informatics and healthcare analytics.

Eligibility: 

• Applicants should hold or expect to gain a minimum of a 2:1 Bachelor Degree or equivalent in Computing and Electronics and knowledge of Mathematical Modelling and Statistical Analysis or a strongly-related discipline.
• Due to restrictions on the funding this studentship is open to UK applicants.

Funding Details:   

• Starts 1^st July 2025
• 3-year award
• UK/Republic of Ireland fees covered plus current UKRI level stipend (£19,237 per year).

How to apply:   

• Apply for a PhD in Biomedical Engineering at https://bit.ly/ReadingPhDApply via the above ‘Apply’ button.  
• Please quote the reference “DRC24-138” in the ‘Scholarships applied for’ box.

Please upload a CV and Cover Letter with your application. If the application system prompts you to submit a research proposal, paste in the project title and move on to the next step.

Application Deadline: 01/03/2025

Further Enquiries:  

Please note that, where a candidate is successful in being awarded funding, this will be confirmed via a formal studentship award letter; this will be provided separately from any Offer of Admission and will be subject to standard checks for eligibility and other criteria. 

For further details please contact:

• Professor William Holderbaum, email: w.holderbaum@reading.ac.uk
• Dr Christopher Blick email: Christopher.Blick@royalberkshire.nhs.uk

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