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for quality and proper format. Makes notation when images are to be repeated, and the proper technical factors needed for correction. Provides patient education prior to, during, and subsequent to the procedure
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The University of Chicago Academic Jobs Research Appointee - Neurovascular Surgery Research Lab #NSU020 Department of Neurological Surgery, Biological Sciences Division Position Type: Other
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Computer Science or Data Science. Experience: Previous data science experience. Preferred Competencies Proficiency in Python and BASH; familiarity with SLURM and PyTorch. Proficiency in machine learning specifically
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: Knowledge of basic computer proficiency including computer programs and standard laboratory equipment. Knowledge of basic programming in a few coding languages. Preferred Competencies Knowledge of regulatory
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Theranostics program —a rapidly advancing field at the intersection of molecular imaging and targeted radiopharmaceutical therapy. This is an exceptional opportunity for a candidate with expertise in nuclear
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(Cell Segmentation, Cell Classification, Community Detection) We analyze CODEX multiplexed imaging data using established, state-of-the-art computational pipelines to detect immunological differences
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computer science, computer engineering, data science, or similar. Technical Skills or Knowledge: Experience with one or more machine learning and deep learning frameworks such as TensorFlow, PyTorch, or Keras
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Accessibility Guidelines. Create alternative text descriptions for images that are accessible with screen reader technology. Convert math content into accessible formats using Math Type and OCR software. Format
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computer science. Experience: Experience in python including torch and scikit-learn libraries strongly preferred. Experience in working with image data or unstructured text data with large language models. Preferred
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of policies and procedures. Participate in developing and implementing QI monitoring. Participate in providing in-service and outreach education program. Act as resource for clinical skills for staff