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Research Scientist leads innovative research initiatives in geospatial science, remote sensing, and GeoAI, applying advanced analytics, machine learning, and image processing techniques to address complex
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researching on improving optical inspection and measurement systems towards higher performance (speed, resolution), robustness and flexibility. We cover the whole data processing chain - from image capture
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outstanding clinical, research, and educational resources in the department and organization, including substantial, dedicated expertise in imaging technology innovation, artificial intelligence, and health
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vivo and In vitro procedures using sophisticated radiation-detecting instrumentation (including SPECT and PET), accomplishes computer processing and image enhancement, participates in clinical and non
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» Computer engineering Researcher Profile First Stage Researcher (R1) Positions Other Positions Application Deadline 20 Oct 2026 - 17:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full
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assessed at each stage of the recruitment process. To be considered for this post, you must also submit a separate online application to the ‘Biomedical Engineering and Imaging Science Research MPhil/PhD
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About Us The School of Biomedical Engineering and Imaging Sciences is an interdisciplinary School dedicated to the development, clinical translation and clinical application of medical imaging
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imaging, nanomedicine and cancer biology The opportunity to contribute to the clinical translation of molecular imaging technology developed by precision oncology company Ferronova 3.5 years funding
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. Evaluate MR scans for technical quality, collate processed images and sequence of acquisition and label appropriately. Schedule patients for procedures; assist with clerical functions. Charge MR procedures
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours 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