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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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affects the performance of plasmonic structures in photovoltaics and imaging. About this position In this position you will leverage materials with high thermal conductivities (e.g. 2D materials) to achieve
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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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-driven model for assessing the reliability of official network maps (KLIC deliveries). You will build a prototype algorithm that can be used by infrastructure and civil engineering professionals to better
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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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Vacancies Postdoc position on deep learning based medical imaging for medical robot Key takeaways In this role, you will help develop and implement cutting-edge AI solutions for real-time, image
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processes. In this project, we will leverage the advanced voltage imaging in larval zebrafish to investigate how intrinsic plasticity reshapes neuronal behavior. Your job Traditional electrophysiological
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representations. In this project, you will substantially improve quantitative magnetic resonance imaging (MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers
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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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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