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guidance and robotics. Our work combines medical imaging, computer vision, and machine learning with strong clinical translation, in close collaboration with Balgrist University Hospital and the national
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intelligence (AI)-assisted image analysis for bioinformatics and medicine. The project is highly interdisciplinary, involving areas of microfluidics, fluidic mechanics, biomedical imaging, and machine learning
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Knowledge of medical imaging Good knowledge of image processing Good knowledge of signal processing Good knowledge of AI for medical imaging Ability to use computer programming tools Ability to use word
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ACTIVITIES IN THE RESEARCH AREA OF DEVELOPMENT OF AN ADVANCED PLATFORM FOR THE DIAGNOSIS AND TREATMENT OF NASAL OBSTRUCTION USING 3D MORPHOMETRY, FLUID MECHANICS AND MACHINE LEARNING AUTOMATIC. (C-059/25
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and p er protocol. Evaluate MR scans for technical quality, collate processed images and sequence of acquisition and label appropriately. Schedule patients for procedures; assist with clerical functions
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inline control system based on Machine learning and simulation models. Conduct experimental studies to validate robotic coordination algorithms, optimized processes, and printing performance. Collaborate
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not yet competitive for 5-year clinician scientist fellowships. This post is designed for applicants with a research interest in machine learning or data science approaches for patient stratification
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. Experience with machine learning or deep learning-based segmentation algorithms. Experience with statistical analysis to interpret quantitative image data and generate biological insights. Experience in
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to work effectively with a team of scientists and students Desired Qualifications* Experience with machine learning/deep learning and computer vision techniques Experience in medical image analysis of 2D
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Institute, research in the Dey Laboratory focuses on automated derivation of imaging measures from noninvasive cardiac image data, clinical implementation of novel automated computer processing algorithms