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innovation come together. It focuses on imaging and image-guided interventions in areas such as oncology and cardiology. This strong collaboration enables a multidisciplinary approach, allowing research to be
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Image Analysis Group (DIAG) at Radboudumc. We develop, validate and deploy novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided
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You will develop and validate advanced AI models that integrate medical imaging, multi-modal clinical and omics data, and explainable AI (XAI) for the prediction of hepatocellular carcinoma (HCC
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bioluminescent imaging with cutting-edge organ-on-chip models, the project aspires to enhance understanding of OA pathology and facilitate the development of targeted therapies. This approach not only aims
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tracers. Specifically, you will use clinical molecular imaging data in combination with numerous methods (i.e., AI image analyses, PBPK modeling, immunohistochemistry, FACS). As a postdoctoral researcher
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Novel Broadband (Visible-to-Shortwave Infrared) CMOS Image Sensor Pixel Architectures Job description The Image Sensor Group in the EIectronic Instrumentation Lab is looking for a postdoctoral
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imaging, multi-modal clinical and omics data, and explainable AI (XAI) for the prediction of hepatocellular carcinoma (HCC). Your research will directly contribute to early detection and risk stratification
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Are you excited about applying AI to solve real clinical challenges? As a postdoctoral researcher in the Mathematics of Imaging & AI (MIA) chair, you will join the ZonMW-funded AI for EVAR project
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://www.academictransfer.com/en/jobs/355391/postdoctoral-researcher-machine… Requirements Specific Requirements You hold a PhD degree in Computer Science, Data Science, Biomedical Engineering, or a closely related field, with a
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Postdoctoral researcher Open innovation in the Healthcare domain Faculty: Faculty of Geosciences Department: Department of Sustainable Development Hours per week: 32 to 40 Application deadline