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scanning using Motic Slide Scanner of stained slides for analysis. Learn and perform quantitative analysis of stained slides using Image J and/or HALO image analysis system. Learn and perform quantitative
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technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques
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of Medical Imaging at SMH, please visit our home page at https://radiology.to/ CAUTION: This ad is “posted only” to the U of T affiliated hospital job board. Please see the information directly above for the
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of wet lab experience. Degree in the biological sciences - biology, biochemistry, pharmacology, ophthalmology, etc. Experience with animal handling, ocular imaging (fundus, OCT), tissue dissection
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(AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of
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Job Code? Yes Standard Hours per Week 40 Full Time or Part Time? Full Time Shift Day Work Schedule Summary Monday-Friday 8:00 am to 5:00 pm VP Area U of U Health - Academics Department 00232 - General
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computer skills including computer documentation and order entry. Demonstrated experience with and knowledge of current medical, surgical, and pharmaceutical treatment modalities of the post-cardiothoracic
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computer skills, including Microsoft Office products and other software applications Ability to work independently and efficiently Ability to travel from point A to point B throughout the workday as assigned
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proper data for billing (ICD codes/CPT). Effectively and efficiently utilize multiple pieces of equipment and computer programs. Complete preliminary reports. Participate in quality assessment (QA
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commitment to carrying out professional responsibilities, adherence to ethical principles, and sensitivity to diversity. Ability to demonstrate computer skills including computer documentation and order entry