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Field
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Ultrasound (UDUS) Research Group and the Michigan Institute for Imaging Technology and Translation (MIITT) at the University of Michigan. Our team is positioned at the interface of ultrasound (US) and magnetic
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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in top-tier conferences and journals Job Requirements: PhD or equivalent in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field. Strong background in IC front-end
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conferences and journals Job Requirements: PhD or equivalent in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field. Strong background in IC front-end design
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imaging. Within our research program, you will perform grant funded research developing novel algorithms or building new dynamic imaging systems that account for patient motion (breathing, cardiac, etc
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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treatment and reducing brain injuries Modern MRI scans tell us about a tumour’s biology. Through advanced computing (radiomics), it is possible to extract much more information from MRI images than is visible
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Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience working with clinical data
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! Key responsibilities will include: Research: Support large-scale cognitive neuroscience research on brain stimulation, imaging, neurofeedback and neuropharmacology; develop a coherent research program