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validating deep learning models for the prediction of disease progression from ophthalmic data. Skills include working with image or computer vision-based toolkits, development of multimodal, multidata type
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collection of over 9,000 pairs of donatedhuman eyes – complete with full genetic profiles, images, and ophthalmic and medicalhistories – and a large study cohort of AMD patients. The Sharon Eccles Steele
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combinations of approaches including electrophysiology, optical imaging, myocyte isolation, cell culture, and molecular biology. Expertise in electrophysiology and imaging approaches is highly preferred
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collaborative efforts among researchers at the University of Utah and UC San Diego in developing and applying methods in predictive and causal modeling of complex biomedical and social processes and systems