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Field
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. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software packages for data
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 7 hours ago
. Description: Uncertainty quantification is a field with wide applicability to the design, development, and science return of space science missions. There is growing interest for the tools and practices
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that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute
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supercomputer, the world's first exascale computing system. This is a unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and
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developing or applying parallel algorithms and scalable workflows for HPC resources. Experience developing or applying privacy-enhancing technologies such as federated learning, differential privacy, and
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learning algorithms Healthcare facility design and research Knowledge, Skills, and Abilities: Excellent verbal and written communication skills, including publications in peer-reviewed journals. Strong
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lead efforts to develop experimental techniques using conventional and coherent imaging in the ultrafast time domain, as well as a computational framework for modeling and reconstructing images
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network modeling to address real-world policy challenges through algorithm development and technical analysis. Key Responsibilities Conduct original research in generative AI Train and supervise graduate
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. Develop algorithms for archiving sea surface temperature data in Group for High Resolution Sea Surface Temperature GDS 2 format. Job Related Minimum Required Education and Experience Requires a Doctoral
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imagery). Experience in building data models using Python or other statistical and/or mathematical programming packages. Proficiency in developing machine learning algorithms to analyze spatial-temporal