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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 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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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 | 16 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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or MD/PhD degree 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
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contributions to biomedical science. Be Bold. Join a research program focused on uncovering the cellular, molecular, and neural mechanisms underlying migraine and chronic pain. You'll leverage cutting-edge
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models (rodent handling/surgery experience a plus). ● Familiarity with quantitative/computational approaches (e.g., R, Python, image analysis, statistics) is a plus but not required. ● Ability
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intelligence and machine learning across several domains of physics and astronomy. The successful candidates will develop an integrated image-processing pipeline and apply it to three distinct problems: rare
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, biomedical imaging, computer vision, and clinical data science. Individuals holding MD or equivalent degrees with at least one year of related computational experience may also be eligible. Under
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experimentation: 70% • Design, perform, analyze, and interpret experiments spanning neuroscience, molecular biology, immunology, genomics, imaging, and behavior. • Develop and troubleshoot new techniques and models