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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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. Preference is given to new PhDs. Accomplished credentials are required in both research and teaching. Letter references for the applicants must include one letter that addresses teaching. For best
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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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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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of the applicant’s qualifications and potential for innovative, ground-breaking independent research and the expected date of completion of the PhD requirements, if still in progress. Applicants should email all
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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