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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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This position is embedded in the Medical UltraSound Imaging Center (MUSIC) of the Department of Medical Imaging of the Radboud university medical center. Within MUSIC we have ample experience in
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laboratory-setting project. Specifically, we will integrate recent advances in artificial intelligence-based automated interpretation of medical images, and new knowledge on the human visual system
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& Computer Science of the Eindhoven University of Technology in the field of “Geometric Learning for Image Analysis”.The two year postdoc position is part of VICI Project (VI.C. 202-031, PI: R.Duits) and will
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technologies including two-photon imaging , MRI, ultrasound, and a self-developed imaging cryomicrotome. Amsterdam UMC offers an inspiring, multidisciplinary, and collaborative research environment. You will
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applications involving image analysis, real-time monitoring, or complex process optimization. You have hands-on experience with model optimization techniques such as post-training quantization (PTQ
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-oriented mindset, and a passion for (scientific) challenges, you are the right person for us. Our lab develops technologies that integrate advanced imaging, computational analysis, and single-cell & spatial
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of what microscopes can achieve. You will create and apply sophisticated algorithms, physics-based simulations, and machine learning models to process complex data from our cutting-edge imaging systems
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now includes five years of follow-up data. You will focus on linking the molecular data with clinical data, which is being analyzed by clinical researchers. Additionally, you may integrate imaging data
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precise cancer removal. Utilizing Artificial Intelligence to Segment Echo Images of Tongue Cancer Intraoperatively to Facilitate Radical Resection Squamous cell carcinoma (SCC) of the tongue is a rare yet