Fetal Ultrasound AI Research Scientist

Fetal Ultrasound AI Research Scientist

Full-Time 40000 - 60000 £ / year (est.) No working from home possible
King’s College London

At a Glance

  • Tasks: Develop and test machine learning models for fetal ultrasound imaging.
  • Company: King's College London, a leader in medical research and innovation.
  • Benefits: Professional development opportunities and a collaborative academic environment.
  • Other info: Join a dynamic team dedicated to advancing medical imaging.
  • Why this job: Make a real difference in healthcare with cutting-edge AI technology.
  • Qualifications: PhD in a related field and strong background in medical AI.

The predicted salary is between 40000 - 60000 £ per year.

King's College London is seeking a Researcher for a full-time post focused on developing and testing machine learning models for identification of fetal ultrasound imaging planes. This role is pivotal in creating AI tools to assist sonographers.

Candidates must hold a PhD in a related field and possess a strong background in medical AI. The position offers opportunities for professional development and engagement in a collaborative academic environment.

Fetal Ultrasound AI Research Scientist employer: King’s College London

King's College London is an exceptional employer, offering a vibrant academic environment where innovation thrives. As a Researcher in Fetal Ultrasound AI, you will benefit from extensive professional development opportunities and collaborate with leading experts in the field, all while contributing to groundbreaking advancements in medical AI. Located in the heart of London, the institution fosters a culture of inclusivity and support, making it an ideal place for those seeking meaningful and rewarding employment.

King’s College London

Contact Details:

King’s College London Recruitment Team

We think you need these skills to ace Fetal Ultrasound AI Research Scientist

Machine Learning
Fetal Ultrasound Imaging
AI Tool Development
Medical AI
PhD in a Related Field
Model Testing
Collaboration Skills