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of dehydration. Upon these experimental study, we will develop a working prototype with all proposed functionalities. The proposed system will be the first wearable dehydration sensor targeting
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: Performs specialized research techniques and procedures related to phenotypic characterization of cardiovascular disease using available signal-based and imaging techniques. Compiles and analyzes data using
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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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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found at: https://www.directives.doe.gov/directives-documents/400-series/0486.1-BOrder-a/@@images/file Equal Opportunity/Affirmative Action Employer Brookhaven Science Associates is an equal opportunity
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/400-series/0486.1-BOrder-a/@@images/file Equal Opportunity/Affirmative Action Employer Brookhaven Science Associates is an equal opportunity employer that values inclusion and diversity at our Lab. We
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related field. The ideal candidates will have experience in one or more of the following topics: deep learning for image and point cloud data processing, deep learning for time series data prediction
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experience, mouse colony management, tissue collection and processing for molecular biology analysis. Molecular Biology: Western blot, Immunoprecipitation, Northern blot, PCR, RT-qPCR, ChIP, RNA-IP, Click-IT
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
imaging, and structured electronic health record (EHR) data. The postdoctoral researcher will work closely with the Director for Cardiovascular Artificial Intelligence Research and contribute to the design
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the development of novel therapies for coronary microvascular disease. The research program focuses on clinical translation and the development and validation of existing and novel cardiac imaging-based