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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 5 hours ago
status Questions about this opportunity? Please email npp@orau.org Qualifications PhD in electrical engineering or a closely related field. Previous laboratory and/or field experience. Experience
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, Assistant Professor of Electrical Engineering Research Project Description: Hydration of the body is a critical physiological health indicator, but it is challenging to measure accurately, especially in a
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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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research program focuses on developing innovative cell-based therapies and model systems for CNS diseases, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and brain cancers. We
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development. Basic Qualifications: A PhD in computer science/engineering, electrical engineering, data science or a related field completed within the last five years. Experience of AI and efficient computing
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supervision of the Principal Investigators/Director of the Program for Sustainable Pavement Engineering and Research (PROSPER) at InTrans and collaborate closely with federal and state departments
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. Basic Qualifications: PhD in physics, applied physics, material science, chemistry, chemical or electrical engineering, or a related discipline completed within the last five years. A background in
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treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We
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treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We
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, is seeking highly motivated candidates for multiple postdoctoral positions. We are specifically looking for candidates who possess a strong background in theoretical and computational modeling