Description of Research Project:
Prognosis in healthcare can be an effective approach to preserve and prolong the wellbeing of individual. Through personal electronic devices, prognosis is achieved by daily monitoring of an individual’s activities. The data acquired can potentially be used for simulating the trajectory of health, providing a means for predictive health monitoring. This can be achieved by establishing a digital twin model of the personalized wearable devices. In this project, we aim to develop digital twin model simulation of mobility health.
Preferred Technical Background:
Ph.D in any engineering discipline including but not limited to computer science, computer engineering, with hands-on experience on data mining, machine learning and/or artificial intelligence.
How to Apply:
Please submit your application including a CV/resume specifying your education background, work experience and technical skills, as well as expected salary and availability to Prof Low at hongyee_low[AT]sutd.edu.sg with Subject “Research Fellow”. Only shortlisted candidates will be notified.