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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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qualifications with a university degree (Master or equivalent) in physics, engineering or computer science Proficiency in computer vision and machine learning with Python Knowledge of X-ray physics and laboratory
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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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, electrical engineering and computer science to design highly efficient and sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients. Project background
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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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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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organs Investigate macrophage dynamics and/or serosal repair mechanisms Analyze imaging data using quantitative and computational approaches Perform spectral flow cytometry and standard bioinformatics
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, deliberately interdisciplinary network spanning planetary physics, geochemistry, chemistry and biology. The position takes two years, but is extendable by a third year subject to NCCR Genesis procedures. Project
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preparation, data visualization, and project reporting, and stay current with emerging single-cell and spatial genomics methods. Profile PhD degree in bioinformatics, computational biology, computational
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physics, quantum engineering, electrical engineering, or closely related discipline You should have a strong motivation to build a quantum computer from scratch Excellent spoken and written English