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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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advancement. The ideal candidate will have a PhD in computer science or related field utilizing computer science methods, strong expertise in medical image processing, registration and analysis and a long-term
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for cardiovascular and thoracic patients, along with advanced imaging. The 690,000-square-foot hospital which also features 20 surgical and three interventional radiology suites is being constructed adjacent to the
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for cardiovascular and thoracic patients, along with advanced imaging. The 690,000-square-foot hospital which also features 20 surgical and three interventional radiology suites is being constructed adjacent to the
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of AI-based computer vision methods on optical and radiologic images. Our laboratory focuses on (1) intraoperative imaging with label-free optical microscopy and (2) neuro-imaging such as computed
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/assisting patients and families, providing check in services for Breast Imaging and X-ray patients, scheduling BI patients for appointments, answering telephone calls and processing orders as needed
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information into patient's charts. Assist and direct patients as needed for the following imaging modalities: General Imaging, Mammography, Computed Tomography (CT), and Ultrasound (US). Upload images from a CD
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of precision imaging datasets using supercomputing cluster resources. Support students and trainees involved in data processing and analysis. Present novel discoveries at international conferences. Publish
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job An NIH-funded postdoctoral position is available for a two-year program in the laboratory of Brendan Dougherty within
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modalities: General Imaging, Mammography, Computed Tomography (CT), and Ultrasound (US). Upload images from a CD. Accurately record and forward phone messages. Consistently uphold the Radiology Gold Standard