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Biomedical Engineering conducts leading research in image analysis, computer vision, and machine learning, with a growing emphasis on generative AI and AI for scientific discovery. Our mission is to develop
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and/or atom probe tomography Experience in image processing Experience in programming with Python or Matlab is strongly desired Team spirit as well as excellent communication and organizational skills
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team of structural biologists and microbiologists to tackle this important fundamental question. The project focuses on cryo-electron microscopy (cryo-EM) studies and computational image processing, and
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recently developed in a commercial 65 nm CMOS imaging process by a large international consortium of engineers and scientists for the ALICE ITS3 upgrade and the future experiments, ePIC@EIC and ALICE3@LHC
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, engineers, computer scientists, nuclear medicine physicians, …) towards the overall aim of enabling translational and physician-in-the-loop AI for medical imaging. Our research team is multicultural and
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synthesis (images, text, audio, video), and complex reasoning. Investigate model compression, quantization, and distillation for efficient deployment. High-Performance AI Infrastructure (Infra): Design and
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have received their MA or PhD at the time of application, has preference for candidates that have experience working with our learning management system, ICON, and has a preference for candidates that
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Professional II position is available in the laboratory of Dr. Russell S. Witte, PhD in the Department of Medical Imaging at the University of Arizona (Tucson, AZ). The successful candidate will assume a lead
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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translation of innovative miniature, hair-thin imaging devices we have previously developed (doi.org/10.1117/1.JBO.29.2.026002 ). These devices are designed to enable early and accurate detection of cancerous