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Field
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; devising scene completion and occlusion-handling algorithms (e.g., using Zero123, OctMAE) to robustly reconstruct partially visible objects, ensuring accurate simulation for both training and test-time
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 months ago
of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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At the Faculty of Engineering and Science, Department of Materials and Production one or more Postdoc positions in the area of Optimization and Algorithm Design are open for appointment from April
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5000 years as a background to the local reconstructions for target sites. This will be achieved using pollen databases, new pollen cores, and the landscape reconstruction algorithm (REVEALS and LOVE
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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analysis across time and conditions Algorithm design and modeling. The role offers significant intellectual freedom and opportunities to shape the direction of the research. Minimum Qualifications: • PhD in
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 months ago
Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and participation in upcoming
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electron beams, advanced beam-manipulation for precise electron-beam shaping, and ML for accelerator science. Responsibilities Develop and deploy ML algorithms for autonomous operations and optimization
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and resilience across heterogeneous computational resources while addressing workflow requirements for scientific applications. Validate distributed intelligence algorithms at scale on ORNL's
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disease progression. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will