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Post-Doctoral Position - Medical Image Processing - (240000Y9) Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 8 hours ago
to misapprehensions about the outer planets and moons. In addition, many images were never processed in to full color and remain monochromatic. Digital image processing has now advanced significantly, permitting new
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reconstruction and processing. Candidates are expected to have a strong background in medical imaging, experience in imaging system evaluation, deep learning and clinical investigation. Brief Description of Duties
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longitudinal consistency and data quality, including parameter tracking, protocol versioning, and rigorous QC frameworks Implementing, validating, and extending image-processing and analysis pipelines
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-, outcome- and sensory-guided actions, and how these processes are disrupted in genetic neurodevelopmental disorder models, including autism, OCD, ADHD, and intellectual disability. Postdocs will work in a
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100% postdoctoral position within the Department of Radiology. The primary focus of this research position is to assist in innovative MR image reconstruction and pulse sequence methods. The successful
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microscopy, and technical writing. Hands-on experience with imaging flow cytometry, brain tissue homogenization, homogenate analysis protocols, and cell separation and lysing methods are a plus. Job Duties
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/ Location Main Campus Address 1235 E. James E. Rogers Way, Tucson, AZ 85721 USA Position Highlights The postdoctoral scholar will conduct research into hyperspectral imaging of geological and mining materials
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neuroimaging acquisition, processing, and quantitative analysis; ● Hands-on experience with fMRI (task-based or resting-state), diffusion MRI, and/or multimodal imaging; ● Proficiency in Python, MATLAB, and/or
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, bioinformatics, production of genetically engineered animal models, single-cell profiling, and advanced image processing and analysis. In addition, numerous institutional shared resources and core facilities