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Assistant Professor of Electrical and Computer Engineering - Medical Imaging (Tenure Track) University of Oklahoma Norman Campus: Gallogly College of Engineering: School of Electrical and Computer
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Education: Ph.D. or M.S. in Computer Science, AI, Computer Vision, or related field Experience: 3+ years in computer vision and deep learning, with specific focus on microscopic imaging, generation
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, Mechanical Engineering, and Surgery & Cancer. What you would be doing: The post will support the multispectral imaging theme of the Hub award, and you will be expected to play a key role in developing and
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coordinator for the Medical Imaging and Radiologic Sciences Sonography Program include working in partnership with the Radiologic Technology clinical coordinator(s) in the management and oversight of clinical
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Klenerman in the Yusuf Hamied Department of Chemistry, from October 2025 for up to 2 years. This is a collaborative project with Professor Clare Bryant in Clinical medicine and aims to image and characterise
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for further development. Mentor students Job Requirements: Master’s degree in civil engineering or related field At least 1 year of relevant experience in signal processing and machine learning. Good written
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processing and image reconstruction. Orange County is world-renowned for its natural beauty, perfect year round climate, gorgeous locales on the Pacific Ocean and incomparable recreational opportunities. Great
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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 image acquisition, processing, analysis, and interpretation Develop and validate new imaging techniques, algorithms, or software to improve diagnostic accuracy and patient outcomes Collaborate with
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available