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Field
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you want to develop new technology for interpretation of images in the field of geoscience? Improve
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Sectional Interventional Radiology fellowship program provides unique advanced clinically rigorous training in Abdominal Imaging, Image Guided interventions and Clinical Research. Imaging training broadly
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biology, engineering, biophysics, computer science) and experience in 3D imaging of brain tissue, image segmentation, and handling large datasets. You are comfortable with machine learning and image
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characterisation and heat-transfer measurements, and development of model-predictive control algorithms for dynamic charge–discharge operation. The postholder will support prototype fabrication, instrumentation
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for funding agencies and stakeholders. Job Requirements: A PhD degree in Mathematics, Geophysics, Physics, Computer Sciences, or related areas. Strong background in numerical modeling and high-performance
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Number: 6693782 Musculoskeletal Imaging Fellowship 2027-2028 University of California Los Angeles Requisition Number: JPF10688 The UCLA Musculoskeletal Imaging Fellowship is a one year program during which
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the ability to translate between clinical and technical language while working with radiology informatics teams. A solid understanding of DICOM standards, PACS and RIS environments, GDPR, and image transfer
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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
of the selected methodologies and approaches; - critically assess the research process and evaluate the results obtained.; 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: The four Research Initiation
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Kuberan Pushparajah and Dr Alessandra Frigiola within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About the role Applications
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imaging under the supervision of Dr Kuberan Pushparajah and Dr Alessandra Frigiola within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London