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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
Lab. We perform molecular biology, genetic crosses, light microscopy, and quantitative image analyses in C. elegans. Because we study living worms, our experimental protocols sometimes require work
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Eligibility criteria - physics with knowledge in optics - knowledge in microscopy - knowledge in single-molecule imaging (acquisition and processing) - knowledge in photophysics - knowledge in cell culture
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. Execute Data Science Workflows: Utilize Montana State University’s Tempest Supercomputer to process large imaging datasets and generate distribution heat maps. Collaborate Across Institutions: Coordinate
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software programs including Microsoft Office (Word, Excel, PowerPoint) · Knowledge of computer programming/scripting (e.g., Matlab, Bash/Unix) · Knowledge and experience using image/EEG
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of the award, awardees will be considered for Assistant Professorship. Awardees will also be assigned a faculty mentor for the duration of the scheme. Application Process Applications are open throughout
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, developing pixel detectors for high-energy physics, telescope cameras, medical imaging systems, and other scientific and industrial applications. We are seeking an outstanding candidate—creative, analytical
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dynamics during regeneration, aging, and cancer, and how these processes can be modulated. Our research is primarily conducted in vivo. We combine genetic mouse models (lineage tracing, conditional
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of dislocation stress fields (in collaboration with CEA Saclay). - Program the diffraction procedures to generate images comparable to Electron Channeling Contrast Imaging (ECCI) obtained using a Scanning Electron
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-phenotyping of individuals with autism and controls including brain imaging (EEG and MRI) and a battery of cognitive tests. Our group is currently developing new methods for analyzing whole genome and brain
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Institutes of Health and the Delaware Community Foundation. The postdoctoral researcher will contribute to the development of novel, fast, and high-resolution MRE imaging methods to characterize brain