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Field
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to expand their scientific expertise while contributing to meaningful discoveries in vision science. What You’ll Bring Required Qualifications PhD or MD/PhD in a relevant scientific discipline. Strong
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, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral, and interpersonal
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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to the group’s open-source software, and participation in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, computer science
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, responsibilities and activities may change at any time with or without notice. Required Qualifications: PhD in immunology, biochemistry or a related field. Experience with standard molecular biology techniques
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Overview RUTGERS CANCER INSTITUTE VISION, MISSION, AND CORE VALUES: VISION: Through our science, our evidence-based actions, our openness, and our respect for those we serve, we will advance cancer-focused
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sensing. Profile PhD in Computer Vision Background in Computer Science Research experience in 3D Computer Vision, remote sensing and aerial imagery Strong computational and analytical skills, as
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, design and implementation of an immersive training tool that leverage spatial computing, computer vision, and on-device AI to support automated feedback, skill evaluation, and scalable surgical and trauma
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have the opportunity to contribute to various cutting-edge research areas. Several exciting research topics are proposed (not limited): Computer Vision / Remote Sensing for Agriculture: Explore
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven