Machine Learning PhD Programme (MLPP)

Machine Learning PhD Programme (MLPP)

Make a meaningful impact
Make a positive contribution to hospitals and patients through AI.

Learn and Master
The opportunity to work with, learn from and share knowledge with uber- smart colleagues in a culture of collaboration and technical excellence. We groom our employees and make sure that they stay at the cutting edge of the technology stack.

Performance Incentives
Competitive pay with share award for top performers.

Progression Path
Well-defined tech career progression path

 

Who Will Impress Us

A strong technical individual with a geeky background like computer science, physics, mathematics who loves programming, solves tough problems, fascinated by Maths and Physics and has a burning desire to build machine learning models.

Machine learning background is not a requirement.

The Candidate

Our aim is to align you with the activities which truly interests you, stretches you technically and helps you grow and impact on billions of patients.

Some of the things you will learn:

Innovate novel models that solve real world problems in the healthcare domain

The models can be forecasting, generative, discriminative, autoregressive, regressive and/or a combination of the above

Work on huge medical datasets from CT, MRI, PET-CT, SPECT-CT, Ultra-sound, X-Ray, Biopsy and many others that encompass over 50 medical disciplines.

Collaborate with the best data scientists in the region, top medical practitioners from prestigious hospitals and top deep learning researchers and advisors from around the world including Harvard and MIT.

Ample research and publication opportunities in the widely coveted arena where AI intersects healthcare.

Desired Education

Bachelors or Masters in Engineering, Computer Science, Mathematics or Physics

Our Commitment to You

Access to senior management

3-tier mentoring system

Overseas learning opportunities

Competitive salary

Contact Us

Give it a shot by sending us your resume and expected salary here.
Shortlisted candidates will be notified within one week.