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Contract type: Fixed term for 12 months Hours: Full-time About the role We are seeking a Full-Time Postdoctoral Researcher in Computer Vision CT image analysis to join the Nuffield Department of Surgical
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Full time, 3 years fixed term, located on the Camperdown Campus at the School of Mathematics and Statistics Join a world-class interdisciplinary team using AI, spatial omics and digital pathology
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, Immunohistochemistry, Tissue microarray, and Digital image analysis. The annual base salary range for this position is $68,500 - $72,500. When extending an offer of employment, the University of Southern California
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input to the project monograph. Present findings at academic conferences, project workshops and policy events. Contribute to digital dissemination, including short-form video explainers, the project
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on development of novel vision-language foundation models for the analysis of digital pathology images. Develop AI agents that use foundation models for the discovery of biomarkers Work in a multidisciplinary team
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University of Southern California - Center for Craniofacial Molecular Biology | Los Angeles, California | United States | 2 months ago
, Tissue microarray, and Digital image analysis. The annual base salary range for this position is $70,304 - $72,500. When extending an offer of employment, the University of Southern California considers
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materials. These systems are instrumented and connected through a unified digital thread platform that captures multimodal, high-frequency data across the full manufacturing lifecycle, from process execution
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-generation Brain Foundation Models as part of the Stanford Digital Brain Project. The fellow will work closely with Professor Ehsan Adeli(link is external) and Professor Dan Yamins(link is external) , as
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. This does not meet the needs of research discovery processes however, as internal researchers likely know the others in their specific discipline and what they’re working on already. Researchers
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image datasets, including hyperspectral, multispectral, thermal, and RGB imagery. Develop field digital twins by integrating crop growth models, remote sensing data, genomic information, agronomic data