Candidate will develop and apply deep learning algorithms to 3D images of the eye (captured with optical coherence tomography or OCT). We aim to develop tools:
1) To improve the diagnosis/prognosis of glaucoma – a major blinding disorder
2) To provide a better definition for glaucoma
3) To de-noise, enhance, and segment 3D OCT images of the eye
The candidate will also join our AI team at NUS (OCTAGON: http://www.bioeng.nus.edu.sg/oeil/OCTAGON.html), and will be expected to interact with engineers, computer scientists, and clinician scientists.
This is an exciting multi-centre project in collaboration with the NUS Departments of Biomedical Engineering and Statistics, the Singapore Eye Research Institute, and 15 glaucoma institutes from 10 countries across 4 continents. Note that our project also has the necessary GPU power that is required to handle 3D datasets.
- PhDs in Computer Science, Electrical Engineering, Biomedical Engineering, Mathematics, Statistics or other related disciplines are encouraged to apply
- Minimum of 2-years experience with deep learning algorithms is required
- Excellent programming skills in Python and experience with Keras are required
- No background in ophthalmology is required, however, the candidate will be expected to become knowledgeable in the field of glaucoma in order to interact with clinicians
Please visit http://www.bioeng.nus.edu.sg/job/research.html for information on application procedure.