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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 19 days 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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between various imaging modalities and multi-omics during aging and development. • Implementing computationally intensive algorithms on high-performance computational clusters
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
Requisition Id 15685 Overview: The Center for Nanophase Materials Sciences (CNMS) is seeking a Postdoctoral Research Associate to support research directed towards developing novel AI/ML algorithms
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Analytics (MSA) Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD), at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Develop algorithms
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setups and develop methods for in-situ diagnostic and monitoring additive manufacturing (AM) processes toward the 3D printing of metal alloys and ceramics. The successful candidate will use optical and
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information efforts in the Nation. The mission is to address challenges facing scalable quantum computing and to develop novel and improved platforms for quantum computation and communication and thus
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resources and collaborating across ORNL, federal agencies, and academic partners. Key Responsibilities: Develop and apply scalable molecular dynamics (MD) and multiscale simulation workflows for biomolecular
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routine background checks. Essential Duties and Responsibilities Neuroimaging data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms
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involving optical imaging, ultrasound systems, and/or contrast agents Develop computational models and reconstruction algorithms for imaging systems Analyze experimental data and prepare manuscripts
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, curate, and analyze field measurement datasets and associated environmental and economic information for model parameterization and validation. Develop or enhance model algorithms simulating carbon and