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Field
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clinicians to rely on CT or MRI. Our recently funded VICI programme, "(R)evolution in Abdominal Ultrasound Imaging", aims to fundamentally transform ultrasound imaging through distributed multi-aperture
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you excited about pushing the boundaries of ultrasound imaging
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We use cookies which are necessary to make our site work. We may also use additional cookies to analyse, improve and personalise our content and your digital experience. For more information, see our Cookie Policy and the list of Google Ad-Tech Vendors . You may choose not to allow some types of...
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A Postdoctoral Research Associate position is available in the laboratory of Basavaraju G. Sanganahalli, PhD, Assistant Professor of Radiology and Biomedical Imaging to work on a newly funded NIH
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. Analyze medical imaging datasets, including image segmentation and interpretation for research applications. Apply advanced computational techniques, including machine learning and deep learning
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and application of advanced computed tomography methods, with a focus on photon-counting CT, quantitative image analysis, and machine learning. The position will involve work across several NIH-funded
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Be You. At Duke, we celebrate individuality and the unique perspectives that each member of our community brings. As the Machine Learning Research Data Analyst, Ophthalmic Imaging, you'll play a
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Classification Title: OPS Research Assistant Classification Minimum Requirements: High School Diploma. Job Description: The Computational Microscopy Imaging Laboratory (CMI Lab), within
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description IPANEMA is recruiting
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Hill seeks a computational postdoctoral researcher to develop and apply methods for integrating single-cell sequencing and imaging data within controlled cell-line model systems. The project focuses