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Field
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validating deep learning models for the prediction of disease progression from ophthalmic data. Skills include working with image or computer vision-based toolkits, development of multimodal, multidata type
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disease states. The candidate will also have the opportunity to work with state-of-the-art equipment such as a small animal radiation research platform (SARRP),cabinet irradiators, and in vivo imagers
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include data preprocessing, literature reviews, running experiments, and contributing to prototype development or analysis pipelines. Will be working with Dr. James Wang for 12 weeks. 7 hours a during
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: Specialization in machine learning and computer vision. Strong skills in developing computer vision and AI models. Experience with thermography or thermal imaging. Experience in data fusion and multimodal learning
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microscopic imaging as needed. Performs lab ordering and maintains laboratory inventories. Assists with inspections and overall laboratory documentation. Maintains lab equipment. Performs other duties and
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team that investigates the the genetic and molecular mechanisms of addiction in a multi-disciplinary approach including genetics, behavior, circuit analysis, imaging, hi-throughput genomics, and
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the cellular crosstalk and basic molecular mechanisms during lung repair and disease. We utilize in vivo mouse genetics, live imaging, 3D organoids, functional screening, and next-generation sequencing
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, confocal, super-resolution, and electron: transmission electron microscopy) complementary expertise in image analysis Hands-on experience with epithelial barrier assessment assays (transepithelial
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of data (15%): Conduct cell culture, live cell microscopy/imaging, high-throughput screening, and quantitative data analysis. Work directly with collaborators and other lab personnel to complete grant
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, 2025 to July 31, 2026. There is some flexibility with the timing. Subsidized housing may be available https://my.cgu.edu/housing/ . The project consists of developing a new paradigm for machine learning