AI-ECG Cardiology Research Fellow

AI-ECG Cardiology Research Fellow

Full-Time 37338 - 44962 Β£ / year (est.) No working from home possible
Imperial College London

At a Glance

  • Tasks: Conduct innovative research on AI-enabled ECGs to enhance patient care.
  • Company: Imperial College London, a leading institution in medical research.
  • Benefits: Gain invaluable experience in a prestigious environment with potential career advancement.
  • Other info: Collaborate with top professionals in a dynamic and supportive research setting.
  • Why this job: Make a real difference in healthcare by improving patient outcomes through AI technology.
  • Qualifications: Background in cardiology or related fields; passion for research and innovation.

The predicted salary is between 37338 - 44962 Β£ per year.

Imperial College London in London is inviting applications for a Clinical Research Fellow in Cardiology to join the NHLI and Chelsea and Westminster Hospital NHS Foundation Trust. The role focuses on prospective studies testing AI-enabled ECGs to improve patient outcomes and care pathways informed by AI insights.

The successful candidate will work with clinicians, scientists, and engineers, contributing to the Clinical Research Facility activities at West Middlesex Hospital.

AI-ECG Cardiology Research Fellow employer: Imperial College London

As a Section Manager at Imperial College, you will thrive in a world-renowned institution dedicated to advancing research for the benefit of humanity. Enjoy a competitive salary and an impressive benefits package, including 41 days of annual leave, flexible working options, and access to on-site leisure facilities. Join a diverse and inclusive work culture that prioritises your personal and professional growth, making it an exceptional place to build your career.

Imperial College London

Contact Details:

Imperial College London Recruitment Team

We think you need these skills to ace AI-ECG Cardiology Research Fellow

Clinical Research
Cardiology
AI-enabled ECGs
Patient Outcomes Improvement
Data Analysis
Collaboration with Clinicians
Scientific Research