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of Department of Ophthalmology in the University of Colorado School of Medicine focuses broadly on quantitative and machine learning techniques in multiple modalities of medical imaging (e.g. fundoscopy images
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of Medicine We focus broadly on quantitative and machine learning techniques in multiple modalities of medical imaging (e.g. fundoscopy images, OCT scans, MRI, CT, X-ray and digital pathology). We bridge
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of hire. MD or PhD. Research expertise in Ophthalmology, Biomedical Engineering, Computer Science, Data Science, Machine Learning One year’s work experience, or equivalent in thesis research and other
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animal models to humans and includes Drs Agrawal, Greene, Klug, Manchaiah, Peng, Rennie, Santos-Cortez, Tollin, Uhler, and others. The ideal candidate for the position will have a Ph.D., MD or MD/PhD
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on the development of artificial intelligence/machine learning algorithms to integrate multiple sources of patient-derived data, such as optical coherence tomography (OCT), retinal fundus photography (RFP), electronic
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of education and related technical/military/paraprofessional experience may be substituted for a bachelor’s degree on a year for year basis. An advanced degree (Masters or PhD) may be substituted
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temporary, non-tenure track positions and will teach no more than two courses per semester. Appointments will be part-time (less than 50%) and will be made semester-by-semester, depending on the needs
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to join our team. Our lab focuses on developing and applying innovative statistical machine learning methods, single-cell multi-omics, and systems immunology approaches to investigate immune-mediated
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including cancer, cardiology, neuroscience, orthopedics, radiology, and transplant. Successful applicants will have deep methodological expertise in AI and machine learning and will lead research programs
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, medical technologies, embedded systems, VLSI, information systems, machine learning, neuro-engineering, and quantum computing. Job Description * Applications are accepted electronically ONLY at www.cu.edu