Sound Analysis for Predicting Category 1 Ambulance Calls The University of Sheffield in United Kingdom

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About this position

I am recruiting a fully funded PhD student to work on the development of voice analysis technologies to improve the triaging of ambulance calls. This project is in collaboration with Yorkshire Ambulance Service and is part of the EPSRC Centre for Doctoral Training in Sustainable Sound Futures.

Funding includes:
- A tax-free stipend of £20,780 per year
- Full coverage of UK home tuition fees
- Research Training Support Grant of £4,100 per year

This is an exciting opportunity for a motivated student interested in AI, speech technology, and healthcare innovation.

For more information or to discuss your suitability, please get in touch as soon as possible. Very short Application Deadline: 21 August 2025

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?? Last opportunity for UK PhD students to join our # CDTSoundFutures cohort in September!

We are accepting applications for the fully funded PhD project "Sound Analysis for Predicting Category 1 Ambulance Calls" at the The University of Sheffield with Dr Ning Ma and Professor Jon Barker and  in collaboration with project partners Yorkshire Ambulance Service NHS Trust

Ambulance call centres are often the first line of defence in life-threatening medical emergencies. In Category 1 cases—such as cardiac arrest or severe respiratory distress—every second counts.

Yorkshire Ambulance Service (YAS) receives over 1.1 million emergency and urgent calls to 999 every year. Skilled call handlers can often identify the severity of a situation within the first 15–20 seconds, but even they face challenges. Factors like high call volumes, stress levels, and variability in experience can impact decision-making—delaying vital interventions.

Emerging technologies are opening new approaches to enhance the triage process. By detecting subtle audio cues—laboured breathing, vocal strain, or signs of extreme distress—AI can help predict Category 1 emergencies faster and with greater precision.

?? The objective of this collaborative PhD project is developing advanced deep learning models for speech and audio analysis. The goal? To integrate AI tools into emergency call centre workflows, improving both the speed and accuracy of responses—and ultimately, saving lives.

?? More project details and how to apply https://lnkd.in/etsDPMif

?? Apply by 21 August 2025

Don’t miss this chance to drive innovation in emergency response technology and help save lives.
# AmbulanceService # 999Calls # HealthcareInnovation # SpeechAnalysis # VoiceTech , # DeepLearning # AIForGood # SustainableSoundFutures

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

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