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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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, including the ability to train staff on new systems, troubleshoot software issues, and manage user access. Experience in inventory management of computers and related equipment Ability to write processes and
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and experience. Completion of the two-year radiologic technology program, approved by the American Registry of Radiologic Technologists (ARRT) and holds a state of Texas state Medical Radiologic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our
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. Describe a deep learning project you have executed. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code repository if possible. If you contributed to a
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., food processing, bioconversion and fermentation processes) Self-supervised learning for multimodal sensor data (e.g., spectroscopy, hyperspectral imaging, 3D point clouds, and other high-dimensional data
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to an Associate’s degree in computer science or related technical field and 2 years of experience in technical support to computer workstations and connectivity to networks. Industry certificates (e.g., A+) may
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work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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Practices, Assistant Dean for Dental Education and Informatics, Assistant Dean for Educational Support and Faculty Development, Assistant Dean for Academic Success and the Assistant Dean for Business
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biology, biological data science, multi-omics, imaging, modelling, and AI-driven approaches PhD candidates will benefit from: Access to state-of-the-art experimental and computational platforms Strong