Hybrid Data Analytics Fellow: AI for Maternal Health

Hybrid Data Analytics Fellow: AI for Maternal Health

Full-Time 29700 - 36300 Β£ / year (est.) Home office (partial)
The University of Edinburgh

At a Glance

  • Tasks: Analyse data from a global study to improve maternal and foetal health outcomes.
  • Company: The University of Edinburgh, a leader in medical research and innovation.
  • Benefits: Gain valuable experience, work with cutting-edge AI, and contribute to meaningful health improvements.
  • Other info: Join a dynamic team at the forefront of medical informatics.
  • Why this job: Make a real difference in maternal health while collaborating with international experts.
  • Qualifications: Experience in data analysis and a passion for healthcare innovation.

The predicted salary is between 29700 - 36300 Β£ per year.

The University of Edinburgh invites applications for a Research Fellow (Data Analysis) in the Centre for Medical Informatics at the Usher Institute. The role supports a global collaborative study using wearable sensors to improve maternal and foetal outcomes during childbirth, analysing real-time physiologic and clinical data from a 13,400-participant trial across 4 countries.

You will develop and apply generative AI methods to predict obstetric complications, work with international partners.

Hybrid Data Analytics Fellow: AI for Maternal Health employer: The University of Edinburgh

The University of Edinburgh is an exceptional employer, offering a dynamic work environment where innovation meets inclusivity. With a competitive salary and comprehensive benefits, employees are encouraged to grow professionally while contributing to cutting-edge research in cyber-security. Located in Glasgow, the university fosters a vibrant community that values diversity and promotes equal opportunities for all staff members.

The University of Edinburgh

Contact Details:

The University of Edinburgh Recruitment Team

We think you need these skills to ace Hybrid Data Analytics Fellow: AI for Maternal Health

Data Analysis
Generative AI Methods
Predictive Modelling
Wearable Sensors Technology
Real-time Data Processing
Collaboration with International Partners
Clinical Data Analysis