PostDoc in Machine Learning for Medical Imaging

University of Southern California
Location: 
Los Angeles, CA, USA
Job Type: 
Full Time
Closing Date: 
Sunday, December 31, 2017

PostDoc in Machine Learning for Medical Imaging

A post-doctoral fellow position in retinal image analysis is available at the University of Southern California (USC) in Los Angeles, California, USA. In this position, the post-doc fellow will have the opportunity to develop innovative machine learning algorithms to analyze OCT imaging data from NIH-funded studies. He/She will have the opportunity to work together with researchers from the Stevens Neuroimaging and Informatics Institute and Roski Eye Institute at USC. Through the Laboratory of Neuro Imaging at the Stevens Neuroimaging and Informatics Institute at USC, the post-doctoral fellow will have access to the ideal environment for medical imaging research (http://www.loni.usc.edu). The USC Roski Eye Institute is a premiere institute of Ophthalmology and home to the largest NIH/NEI funded epidemiologic studies of eye disease in the United States including the Los Angeles Latino Eye Study and African American Eye Disease Study. The ophthalmic imaging division has all of the state-of-the-art imaging devices including commercially available spectral domain optical coherence tomography devices from multiple vendors, wide-field imaging cameras, ultrasound, microperimetry and conventional visual fields, multifocal and full-field ERG as well prototype swept-source OCT and hyperspectral imaging devices.  More information can be found at http://eye.keckmedicine.org/.

The successful candidate should have a PhD in engineering, computer science, or applied mathematics. Related backgrounds in machine learning and medical image analysis are strong plus. Solid programming skills in C++ and Matlab are desirable. Interested candidates please send their CVs to Dr. Yonggang Shi (yshi@loni.usc.edu) and Dr. Amir Kashani (ahkashan@med.usc.edu).