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Postdoctoral Fellow – Deep Learning for 3D Medical Imaging

February 13, 2018

 

 

 

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.

 

REQUIREMENTS:
- 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

 

CONTACT:
Please visit http://www.bioeng.nus.edu.sg/job/research.html for information on application procedure.

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Association des doctorants de Tours : Université François Rabelais | 60 Rue du Plat d'Etain - 37041 Tours, France

 

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