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duties will include method development and validation, as well as potential product screening in a range of FDA-regulated products. Candidates will have the opportunity to interact with a variety of state
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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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(developed from satellite observations, ground monitors, and numeric modeling) with adverse birth outcomes including low birthweight, preterm birth, hospital service use, and mortality. Essential Functions
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(e.g., electrolyte transport properties) and cell-level (e.g., separating electrode- and particle-scale) processes. Methods such as EIS, GITT, pulsing, and others may be used. The position will be in
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to the design of experiments for parameterization of material-level (e.g., electrolyte transport properties) and cell-level (e.g., separating electrode- and particle-scale) processes. Methods such as EIS, GITT
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of complex biopharmaceuticals and vaccines. Projects encompass methodology development, including data analysis, method harmonization and case study applications of state-of-the-art biomeasurement techniques
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Park, the University of Maryland, Baltimore, and the National Institute of Standards and Technology. IBBR leverages state-of-art integrative methods for bioanalytical, biophysical and structural
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(multiphase flow, phase change materials, nanoscale transport), microfabrication, electrochemistry, microfluidic visualization methods, CFD/2-phase simulations, nanoscale thermal/electrical mobility simulations