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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
Posting Information Posting Details Department Biomedical Res Imaging Ctr - 426001 Posting Open Date 05/15/2026 Application Deadline 07/07/2026 Open Until Filled No Position Type Postdoctoral
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Researcher will lead and support experimental research on visual and perception and decision-making in complex environments, with a focus on medical image perception and Artificial Intelligence (AI
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coastal hotspot areas, will embark on this innovation journey. Working within stakeholder alliances based on trust, they will co-design regenerative resilience visions, chart adaptation pathways, and
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time-of-flight secondary ion mass spectrometry (ToF-SIMS), scanning electron microscopy (SEM), and X-ray diffraction (XRD). Experience in data reduction of big spectroscopy, mass spectrometry, and image
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for self-driving and/or human-in-the-loop experiments; (3) computer vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading
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19 Jun 2026 Job Information Organisation/Company Computer Vision Center Research Field Computer science » Other Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application
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identifying the ideal HWO spectral range(s) and resolving power(s) for understanding terrestrial and sub-Neptune planetary environments using high contrast imaging techniques. Candidates working anywhere in
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against different operation conditions. The position is a part of a research project and prototype battery modules will be produced by one of the partners. The tasks include testing of these prototype
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data and report findings in papers. Visa sponsorship is not available for this position. Outstanding U of A benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and
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-resource infrastructure. A partnership with Banner – University Medical Center Tucson and access to the UA Cancer Center's shared resources in genomics, tissue acquisition, biostatistics, molecular imaging