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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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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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(e.g., PyTorch, TensorFlow, JAX), and scientific libraries (e.g., NumPy, SciPy, scikit-learn) Familiarity with medical images such as x-ray, CT, or fluoroscopy. Proficiency in Python coding language and
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implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning
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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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Vacancies Postdoc Position: Multi-Modal AI for Early Detection of Liver Cancer Key takeaways You will develop and validate advanced AI models that integrate medical imaging, multi-modal clinical and
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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
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of Imaging & AI (MIA) chair, you will join the ZonMW-funded AI for EVAR project, aiming to transform the care for patients with abdominal aortic aneurysms (AAA). You will develop and validate cutting-edge