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-learning, deep-learning, chemometric, or related computational methods to imaging, spectral, sensor, process, environmental, or other complex scientific data. Strong quantitative data-analysis and scientific
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with clinical research experience, or a PhD degree in biomedical engineering, medical physics, computational science, or a related field with experience in vascular imaging research. Experience in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
Demonstrated research experience in machine learning, deep learning, medical image analysis, computer vision, biomedical data science, or a closely related area. Strong programming skills in Python and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
Demonstrated research experience in machine learning, deep learning, medical image analysis, computer vision, biomedical data science, or a closely related area. Strong programming skills in Python and
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processing, machine learning, computational imaging, and clinical translation. Beyond your individual research contributions, you will serve as a technical coach for the PhD researchers, helping to align
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collaboratively with others and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications. Communication: Strong and clear written and
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 15 days ago
. The Durability, Damage Tolerance, and Reliability Branch (DDTRB) conducts a broad-based research and technology program that quantifies behavior, durability, and damage tolerance of structural materials; develops
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appropriate statistical and computational methods. Prepare manuscripts, presentations, fellowship applications, and contributions to research proposals. Collaborate across engineering, cancer biology, and
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confocal microscopy, and quantitative fluorescence imaging, to monitor and quantify protease activity in real time. 4. Data analysis and interpretation Processing, analyzing, and interpreting experimental
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measurements, including confocal microscopy, and quantitative fluorescence imaging, to monitor and quantify protease activity in real time. 4. Data analysis and interpretation Processing, analyzing, and