[visionlist] Post-doctoral position available at UCSD Hamilton Glaucoma Center

Chris Bowd cbowd at glaucoma.ucsd.edu
Thu Mar 15 23:48:04 GMT 2012


We are seeking an individual who is interested in developing and employing new machine learning-based techniques to predict and detect glaucomatous progression from information available in optical imaging (e.g., confocal scanning laser tomography, spectral domain optical coherence tomography) and visual field (e.g., standard and frequency doubling-technology perimetry) data. We have an available database of measurements from hundreds of patient eyes tested for up to 10 years on commercially available devices on which we can develop and test classification methods. Our department at UCSD offers an excellent working environment for machine learning research because of our close alliance with the UCSD Institute of Neural Computation and the Salk Institute. The candidate also will have the opportunity to participate in collaborative glaucoma-related clinical research with other clinical research faculty.

The ideal candidate should have a strong background (i.e., Ph.D.) in machine learning, medical informatics, bioinformatics, or a closely related field plus programming experience in Matlab (preferably) and/or C++. Strong statistical experience, strong writing skills, and a history of productivity and independence are desirable. This research is NIH funded and salary will be set according to the NIH post-doctoral scale. Start date is flexible, but the sooner the better.

Please send C.V., research experience/interests, references and any questions via email to:

Christopher Bowd, Ph.D. (cbowd at glaucoma.ucsd.edu)

and/or

Michael H. Goldbaum, M.D. (mgoldbaum at ucsd.edu)
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