Postdoc position in Deep Retinal Image Analysis

UCSD
Location: 
San Diego , CA
Job Type: 
Full Time
Closing Date: 
Wednesday, February 28, 2018

 

Postdoc position in Deep Retinal Image Analysis at Shiley Eye Institute , University of California , San Diego.

 

We are looking for an Independent researcher to develop deep structural analysis of 2D/3D retinal images including 2D fundus images, 3D spectral domain optical coherence tomography (SD-OCT), OCT Angiography and other imaging modalities.

Candidates required to work closely with a multidisciplinary team of UCSD computer scientists, clinical researchers and ophthalmologist from Shiley Eye Institute and other data centers to use state of the art deep learning techniques along with computer vision and pattern recognition methods to develop new methods for retinal pathologies detection.  The candidates should be familiar with machine learning concepts and use detected pathologies as a feature to diagnose different retinal diseases including diabetic retinopathy, age-related macular degeneration and glaucoma. Highly motivated candidates will also receive training and guidance in writing research grants.

Initial appointments will be made for 2 years with a possibility of extension.
 

==== Key Requirements ====

The successful candidate should have a PhD degree or equivalent in Computer Science , Electrical engineering, Biomedical imagining  or related discipline and be able to demonstrate good mathematical, algorithmic and strong programming skills in  MATLAB, Python and C/C++.  Knowledge and experience in one of the deep learning platforms such as Caffe, Theano, Tensorflow or Torch is desirable.

Excellent writing skills, and history of productivity including publication in top conferences or journals such as CVPR, ICCV, ECCV, MICCAI, TIP and PAMI is a big plus. Applications from individuals with disabilities or other underrepresented groups are particularly encouraged. Applications will be accepted until filled.

==== How to apply ====================

Qualified applicants should respond by email as soon as possible to Dr. Goldbaum (mgoldbaum@ucsd.edu) with a CV and top 3 publications.