Jon Barker
1 year ago
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Sound Analysis for Predicting Category 1 Ambulance Calls The University of Sheffield in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded PhD position with a tax-free stipend of £20,780 per year, full coverage of UK home tuition fees, and a Research Training Support Grant of £4,100 per year.
Deadline
Aug 21, 2026
Country
United Kingdom
University
University of Sheffield
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About this position
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
Fully funded PhD position with a tax-free stipend of £20,780 per year, full coverage of UK home tuition fees, and a Research Training Support Grant of £4,100 per year.
What's required
Applicants should be motivated and interested in AI, speech technology, and healthcare innovation. Specific entry requirements are not detailed, but a strong background in computer science, engineering, or a related field is likely preferred. UK home students are eligible for full tuition coverage. No explicit mention of GPA, language tests, or other criteria.
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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