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and learning theory, alongside applied technologies, such as machine learning, pattern recognition, and perceptual information processing, in addition to the classical theory of computation
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of creating robust radio frequency fingerprinting (RFF) systems using machine learning. The successful candidate will have significant experience in signal processing or machine learning, and an outstanding
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researcher with strong skills in artificial intelligence, machine learning, deep learning, and computer vision, with the ability to apply these methods to ultrasound image/video analysis and biomedical data
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reconstruction, processing and quality-control tools in a transparent and reproducible way. You will have the opportunity to: Develop a modern, open and extensible software ecosystem for optoacoustic image
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Magma Research Associates / Magma Research Fellows to develop and maintain the Magma computer algebra system (http://magma.maths.usyd.edu.au/magma/ ). These positions are based at the University
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image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed to ample
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Life Support certification via AHA within 90 days of hire Physical Requirements The physical requirements for this position include regularly sitting at computer workstation for extended periods
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. Experience in experimental work, data collection, and system troubleshooting is desirable. Familiarity with ultrasound imaging, biomedical instrumentation, image processing, or machine learning is desirable
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intelligence, data science, medical physics, neuroimaging, bioengineering, or related disciplines, accompanied by accredited training in machine learning, deep learning, or medical image analysis. Experience: A
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buildings/classrooms spread across both campuses, capturing and/or streaming live on-campus classes, assisting faculty with computer applications immediately during live lecture capture classes, and ensuring