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well as university partners on coastal methods and validation strategies. Mentor summer students on data analysis and visualization workflows. Publish in peer-reviewed journals, present at scientific conferences, and
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immunofluorescence, in situ hybridization, genotyping, quantitative PCR, micro-computed tomography, fluorescent and confocal microscopy imaging, cell culture, and computer based data analysis. Digital PCR and new
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combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. For more information about the total announced post-doctoral
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/Administrative Internal Number: 500774 Job Summary: The Postdoctoral Research Associate will work in the Kinesiology department and will be responsible for leading data collection and analysis in conjunction with
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livable cities. The ideal candidate would have strong experience in some of the following areas: quantitative and qualitative data collection and analysis, geospatial data analysis, urban design, data
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management, workflow systems, analysis and visualization technologies, programming systems and environments, and system science and engineering. Major Duties/Responsibilities: The position requires
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
are of particular interest. The candidate will also develop or improve software for the analysis of these unique MRI data, such as object detection, motion correction, and denoising. These novel MRI tools will be
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quantitative modeling and data analysis. Proficiency in at least one of the following: hydrologic modeling, energy systems modeling, systems simulation, or machine learning/AI. Ability to work effectively on
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biological data. · Proficiency in R and/or Python for data analysis and visualization. · Experience working with large datasets in an HPC or cloud computing environment. · Demonstrated ability to work
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data analysis skills including programming in R, Python, or similar, and proficiency in using GitHub and other data management tools; ● Experience summarizing and visualizing data in accessible and