Research Fellow, Ophthalmology
Research Fellow – Using AI and Biomechanics to Predict Vision Loss Progression from Glaucoma – NUS Department of Ophthalmology, Yong Loo Lin School of Medicine
Job description: We are looking for a bright, dynamic, and highly motivated individual to perform research in AI and translational biomechanics with applications to ophthalmology.
The proposed study aims to use artificial intelligence (CNNs, GANs, auto-encoders, reinforcement learning, etc) and other computational tools (e.g. finite element analysis) to predict vision loss progression from glaucoma. For this project, the successful candidate will use, improve and develop AI and Computational Biomechanics algorithms that can be applied to 2D and 3D medical images of the eye (such as those captured with OCT, OCTA, etc). This work will be performed under a multidisciplinary project called RAMP (Retinal Analytics via Machine learning Aiding Physics) in collaboration with SERI, SMART, MIT, and A*STAR. The successful candidate will be expected to interact with such a multidisciplinary team on a daily basis, and therefore strong communication skills are required. The candidate will be co-supervised by Dr Michael Girard (SERI) and Prof Aung Tin (NUS Ophthalmology).
Qualification: Excellent programming skills (in C++ and Matlab/Python) are required. The candidate is also expected to have a strong foundation in computer vision, artificial intelligence, machine learning, especially deep learning (using e.g. Keras, PyTorch). Knowledge of computational biomechanics techniques (e.g. finite element) is a plus. Knowledge of optical coherence tomography, and Ophthalmology is also considered a plus. Candidates with PhD in Biomedical Engineering, Computer Science, Mechanical Engineering, Civil Engineering, or other related disciplines are encouraged to apply.
Earliest Starting Date: Now.
Duration: 3 years.
Please apply with a detailed CV and the names of two references.
Location: Kent Ridge Campus
Organization: Yong Loo Lin School of Medicine
Department : Ophthalmology
Employee Referral Eligible: No