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models Experience with Pytorch, MONAI, CUDA or equivalent software libraries for developing deep learning models. Familiarity with medical image such as MRI, CT, or volumetric ultrasound. Knowledge
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. Preferred Qualifications: Strong background in ultrasound imaging Experience in photoacoustic imaging Strong hands-on skills in medical device development or strong computational skills including signal
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Experience with Pytorch, MONAI, CUDA or equivalent software libraries for developing deep learning models. Familiarity with medical image such as MRI, CT, or volumetric ultrasound. Knowledge on common medical
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libraries for developing deep learning models. Familiarity with medical image such as MRI, CT, or volumetric ultrasound. Knowledge on common medical imaging data augmentation techniques for robust model
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research aims to develop new AI for shared human-AI decision-making in healthcare imaging. This post is focused on AI-assisted ultrasound guidance building on the group’s prior work on video and multi
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, you will play a central role in developing and validating a novel control strategy for bionic limbs based on real-time ultrasound imaging. Your key responsibilities will include: Designing and
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candidate will have expertise in therapeutic and/or diagnostic ultrasound and will have the opportunity for training through projects developing image-guided/feedback-controlled ultrasound therapies
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
in vivo ultrasound imaging to musculoskeletal modeling and intramuscular electromyography. The position is funded for an initial period of 1 year. However, we are deeply committed to the training and
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healthcare imaging. This post is focused on AI-assisted ultrasound guidance building on the group’s prior work on video and multi-modality ultrasound analysis. The appointee will be part of the Noble research