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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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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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(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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of images (like in comics) in relation to the structure of languages. Additional information about this research project can be found at www.visuallanguagelab.com/pictree . Your position The PICTREE Project
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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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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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well as working with organ-on-chips and imaging of these devices will be considered as a benefit; Excellent analytical skills and an innate ability for solution oriented problem solving; Team player with great
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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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in Data Science, Artificial Intelligence, Computer Science, Cognitive Science, or any another relevant discipline. Have interest and experience with deep learning and image analysis. Have interest and