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-EELS, STEM-EDS, electron diffraction, and 4D STEM, is essential. Experience with in situ gas phase TEM and low-dose imaging. Experience synthesizing polysiloxanes, processing thin polymer films, and
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-distance collaborative autonomy; ● Autonomous Unmanned Systems: aerial robotics, robot motion planning, digital twin development, robot navigation of complex terrain, and simulation-based verification
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bi-parental mapping analysis. Machine Learning and Statistical Analysis: Proficient in conducting and troubleshooting machine learning analysis using large image or numerical datasets for disease
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of Business, which collaborates closely with industry, government, and other key health system stakeholders. The research at CHIDS seeks to understand how digital technologies can be more effectively deployed
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on the coupled thermodynamic, kinetic, and transport processes taking place in the cell. In addition, the successful applicant may contribute to the design of experiments for parameterization of material-level
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transient mathematical models for cell charge and discharge, based on the coupled thermodynamic, kinetic, and transport processes taking place in the cell. In addition, the successful applicant may contribute
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on reports and computer screens, ability to type on keyboard for extended periods.The majority of work is computer-based and is non-labor intensive. Diversity Statement: The University of Maryland, College