The Retinal Analytics via Machine Learning Aiding Physics (RAMP) is an Intra-Create grant hosted by the Campus for Research Excellence and Technological Enterprise (CREATE) and funded by the National Research Foundation (NRF). The principal investigators constitute an interdisciplinary group of ophthalmologists, biophysicists, bioengineers, data scientists and optical scientists working collaboratively, based at three Singapore research institutes: Singapore-MIT Alliance for Research and Technology (SMART), Singapore Eye Research Institute (SERI), the National University of Singapore (NUS) and the Agency for Science, Technology and Research (A*STAR).
The topic of RAMP’s research is ocular biomechanics, in particular relating first principles to statistically confident forecasts of glaucoma progression in patients.
This will be accomplished via biomechanical analysis informed by data science, experiments in micro-structured physical emulators (phantoms) and patient studies. The resulting physical models and algorithms will enable rapid and reliable forecast of whether glaucoma progression will be fast or slow, and better targeted treatment decisions.
For this collaborative project, the selected candidates will have expertise in Artificial Intelligence, Machine Vision, Deep Learning, Soft Tissue Biomechanics, Computational Biomechanics, and Biomedical Imaging (especially Optical Coherence Tomography).
- PhD / DSc or equivalent in ophthalmology; biophysics or physics; mathematics, statistics or data science; materials science or engineering; electrical, mechanical or biomedical engineering; or related interdisciplinary programmes of study.
- A strong publication record commensurate with the candidate’s experience is expected, as well as commitment to research at the frontier.
- Copies of up to three (3) representative peer-reviewed publications along with the application and brief research statement on how you anticipate your research experience and career goals to be relevant to RAMP’s research along with the application
To apply, please visit our website at: http://smart.mit.edu/careers/career-opportunities. Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.