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imaging. The successful candidate will therefore be working primarily as an AI/image-processing researcher, developing deep-learning models for medical images.
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100%, Zurich, fixed-term The X-ray Imaging Professorship develops advanced imaging techniques at the synchrotron and strives at the translation of novel imaging approaches to medical devices in a
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collections of images and associated metadata. These projects involve methods such as image embeddings, similarity search, clustering, computer vision, and multimodal AI. Across both areas, research assistants
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science or Physics You have developed a keen interest in medical imaging physics, signal and data processing Very good programming skills (C, Matlab/Python, TensorFlow/PyTorch) and a passion for both theoretical and
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-vision-based image analysis. Job description Develop the existing functional prototype into a robust, user-friendly measurement system suitable for use in an industrial shop-floor environment. Design and
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, Human-Robot Interaction, Imaging Technology, Machine Learning, Medical Informatics, Medical Robotics, Natural Language Processing, Neuroinformatics, Optimization, Physical AI, Probabilistic Models
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and repair, with a focus on the mesothelium, serosal cavities, and the liver. Using intravital imaging, we track cell behavior and dynamics in real time within living tissue, linking cellular mechanisms
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modeling, laboratory experiments, and theoretical analyses, we seek to link microscopic processes with the macroscopic behavior of both engineering and natural systems and develop predictive tools
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to advanced X-ray imaging applications. The SNSF-funded project ABSOLUTE (nAnoassemBled catalySt and electrOchemicaL processing for hUge aspecTratio microstructurEs) focuses on developing an innovative catalyst
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, networking, storage performance, checkpointing, and scheduling Support the Apertus serving stack, which builds on the same images (operation of the serving stack is owned by a separate engineer) Profile