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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
Posting Information Posting Information Department Biomedical Res Imaging Ctr-426001 Career Area Research Professionals Is this an internal only recruitment? No Posting Open Date 01/20/2026
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simulation of scenarios with different materials and geometries. - Support the development and implementation of signal and image processing algorithms, including fast inversion techniques, FFT, and nonlinear
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high dynamic range (HDR) imaging is redefining the way smartphone cameras and displays capture the world. Despite HDR becoming the new standard, many classic image-processing algorithms and generative
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Responsibilities Design, assemble, and optimize optical experimental setups (femtosecond laser illumination, PMT imaging/detection, opto-mechanical components) to evaluate new technological concepts related
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computer vision, where the PhD project was fully or substantially method-focused on computer vision and/or AI-based image or video analysis have very strong knowledge of machine learning, with practical
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Eligibility criteria Instrumental optics and imaging (microscopy, camera detection) for biology. Skills in coding and experiment control. Basics of machine learning and/or signal processing. Teamwork
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-driven hypotheses into experimental designs. Plan, execute, and oversee experiments across multiple modalities (e.g. proteomics, biochemistry, biophysics, metabolomics, imaging). Design efficient
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for issues presenting at main reception. The LSC is an ambassador of the DFCI patient experience while efficiently managing the patient check-in process; uploading outside imaging into Epic, being responsible
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tomography and will include using and advancing 3D/4D image quantification for such materials/data plus establishing experiment/data-analysis pipelines. You will develop your own experiments as well as working
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teaching faculty in Computer Vision and Image Processing to lead the course, "Machines that see," which introduces students to core computer vision concepts, a vital area of AI. This role involves delivering