Xin Li
1 year ago
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Cardiovascular Research University of Leicester in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded: UK tuition fees and stipend for the duration of the PhD. Only 2 out of 5 shortlisted projects will be awarded funding, making this a competitive call.
Deadline
Expired
Country
United Kingdom
University
University of Leicester
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About this position
Funding details
Fully funded: UK tuition fees and stipend for the duration of the PhD. Only 2 out of 5 shortlisted projects will be awarded funding, making this a competitive call.
What's required
Applicants should have a strong interest in AI, digital health, and improving patient outcomes. A background in biomedical engineering, computer science, or a related field is preferred. Specific degree level, GPA, or language requirements are not mentioned.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Professors
Lecturer
United Kingdom
Research Interests
Cardiology
Medical Imaging
Cardiac Ablation
Electrocardiography
Electrophysiology
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Project title:
Personalised Prediction of Sudden Cardiac Death Using LifeMap Features and Deep Learning
Supervisors: Xin Li and André Ng
Based at the University of Leicester
Funding: UK tuition fees + stipend for the duration of the PhD
This project focuses on developing next-generation risk prediction models for sudden cardiac death (SCD), using wearable-derived LifeMap features and advanced deep learning techniques. It's a great fit for someone passionate about AI, digital health, and improving patient outcomes.
Important: This is a competitive call — only 2 out of 5 shortlisted projects will be awarded funding.
Learn more and apply here:
https://lnkd.in/eVrmjqdj
If this sounds like the right opportunity for you — or someone you know — we’d love to hear from you. Please share!
# PhDOpportunity # CardiovascularResearch # DeepLearning # SuddenCardiacDeath # WearableTech # DigitalHealth # BHF # UniversityOfLeicester # CRE # BiomedicalAI