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project quantifying plant anatomical diversity, the developmental processes that generates this diversity, and how this anatomical diversity influences biomechanical properties. The ideal candidate will
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into the power grid. The successful candidates will support projects on the planning, operation, and control of future power grids accounting for renewables and electrification to achieve clean energy goals using
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
, dynamical systems, and scientific computation. Ideal experimentalists will have strong skills in experimental fluid mechanics, including laboratory design, high-speed imaging, flow visualization, and
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design and build custom, non-commercial apparatus compatible with synchrotron scattering and imaging techniques at the Advanced Photon Source. Candidates with prior experience in developing operando
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imaging. A successful postdoctoral candidate should have a Ph.D. in the relevant field with a strong background in LC-MS/MS. Some bioinformatics expertise is preferred but not required. More details about
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radial velocity spectrometer, wide-field imagers, the Hydra multi-object spectrograph, and other instrumentation. They will also have direct use of the outstanding IU information technology infrastructure
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to extracellular matrix, macrophages · Prior experience with: o Advanced cellular imaging techniques, including live-cell imaging o Coding/bioinformatics analyses o 3D and/or organoid models o
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, proficiency in standard molecular biology and biochemical techniques, experience with 3D image processing and modeling software for structural analysis (such as IMOD and UCSF Chimera). A strong background in
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the internal application process. Welcome to The Ohio State University's career site. We invite you to apply to positions of interest. In order to ensure your application is complete, you must complete
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systems. Essential Duties and Responsibilities: Develop and implement artificial intelligence (AI) and machine learning (ML) techniques for power system planning, operation, control, and cybersecurity, with