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Field
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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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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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quality that is not visible in blood or clinical characteristics. By combining the results of AI-driven image analysis of histological samples conducted in this PhD project with biomarker data and outcome
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scientists, clinicians, and engineers to push the boundaries of brain imaging and contribute to insights that can improve healthcare practice. Technical PhD Candidate In this role, you will be responsible
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intelligence-based automated interpretation of medical images, and new knowledge on the human visual system into the screening mammography reading process. Combining these new capabilities and new knowledge has
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deliveries). You will build a prototype algorithm that can be used by infrastructure and civil engineering professionals to better evaluate cable and pipeline location data. Your tasks will include: 1
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This position is part of the NWO KIC Smart Materials project, Smart Materials for Information Processing, in collaboration with the NanoElectronics (NE) group at the University of Twente and the
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imaging systems capable of penetrating fog, dust, and even certain solid materials. These systems will deliver detailed, high-resolution imaging in challenging conditions where conventional optical sensors
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excitability, have been shown to be necessary for memory formation. Still, it remains unclear how intrinsic plasticity contributes to memory encoding and alters cognitive processes. In this project, we will
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on the development, optimization, and clinical evaluation of new x-ray-based imaging methods. The lab focuses on the use of medical physics approaches to improve image acquisition methods and processing algorithms