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learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In this role, you will
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settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on obtaining external funding and project
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, applied mathematics, artificial intelligence, or a related field. Strong skills in deep learning (e.g., PyTorch/TensorFlow). Experience in Computer vision (3D, detection, classification, segmentation
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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep
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, imaging even several cubic microns of brain tissue yields large image volumes. A key focus of this project is the development of innovative computational methods for the segmentation and geometric
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deep learning, and an understanding of applied mathematics, focusing on algorithm design and analysis. Proficiency in modern ML techniques, including geometric deep learning, diffusion models, and neural
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charter for promoting women’s careers in STEMM subjects (science, technology, engineering, mathematics and medicine) in higher education. The School holds a Silver Award for their commitment
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) mathematics, physics, or a related STEM fields. Job Description: The Division of Biomedical Informatics and Data Science (BIDS) within the Department of Health Outcomes and Biomedical Informatics (HOBI
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equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep learning, or signal processing; familiarity with
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Details Position Description The Engineering & Mathematics Division of the School of Science, Technology, Engineering & Mathematics (STEM) at the University of Washington Bothell (UWB) invites applications