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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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properties from telescope data. The design of robust uncertainty quantification tools is a core component of this effort. -On the experiment design side, the group develops simulation and optimization
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, statistics, or applied mathematics that could drive the frontier of biomedical research. The role will be focused on the development of novel computational and algorithmic methods, with a strong bent towards
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Responsibilities will vary depending on the Fellow’s background, but may include: Developing machine learning, optimization, or simulation models to improve clinical operations and resource allocation Advancing
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between various imaging modalities and multi-omics during aging and development. • Implementing computationally intensive algorithms on high-performance computational clusters
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industrial imaging data. You will directly contribute to developing and deploying algorithms for multi-modal tomography (X-ray, neutron, and electron), advancing methods for non-destructive evaluation (NDE
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, containerization (Docker), Kubernetes API development and web-based analytics tools Systems, Optimization, and AI ML/AI for mobility prediction and optimization Graph algorithms, network science Spatiotemporal
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research knowledge by participating in educational opportunities; reading professional publications; maintaining personal networks; participating in professional organizations. · Use and continually develop
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partners in the digital health and health delivery ecosystem. Research Responsibilities Responsibilities will vary depending on the Fellow’s background, but may include: • Developing machine learning
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uncertainty quantification. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and