4 distributed-computing Postdoctoral positions at The Ohio State University in United States
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background in analyzing large astronomical datasets is essential, particularly in characterizing non-isotropic distributions and spatial-kinematic properties using Gaia and/or DESI data. Proficiency in
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will also be considered. Strong background in analyzing large astronomical datasets is essential, particularly in characterizing non-isotropic distributions and spatial-kinematic properties using Gaia
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that govern time-dependent spectral energy distributions of black hole accretion disks, applying these models to X-ray and multi-wavelength data to extract empirical constraints on accretion flow physics, and
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foliar fungicide studies in soybeans. Develop and apply spatial models to analyze the distribution and spread of soybean pathogens in Ohio, leveraging open-access tools like R and QGIS to visualize and