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-Phenomenology (hep-ph) , High Energy Physics , High Energy Theory , Machine Learning , Neutrino physics , Particle , Particle Physics , Particle Theory , QCD , Theoretical high energy physics , Theoretical High
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, France [map ] Subject Area: Machine Learning / Machine Learning Appl Deadline: 2025/12/12 11:59PM ** (posted 2025/10/21, listed until 2026/04/21) Position Description: Apply *** the listing date
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, France [map ] Subject Areas: Mathematics Statistics Probability Statistical Physics Machine Learning / Machine Learning Appl Deadline: 2025/12/20 11:59PM (posted 2025/11/25, listed until 2026/05/25
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours 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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on topics including mathematical foundations of data science and statistical/machine learning, with an emphasis on inverse problems and in-context learning for PDEs and interacting particle systems
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) and genetics data which are measured by longitudinally and cross-sectionally. • Developing and applying machine learning and AI approaches to identify interactive topological relationships
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-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating environment due to an active in-house workshop
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National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | about 2 hours ago
to advance use of foundation models for Earth Science research and applications, including fine-tuning experiments Use of remote sensing, models, and/or machine learning to further our understanding
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22.12.2025, Wissenschaftliches Personal We are an interdisciplinary team at the Chair of Safety, Performance and Reliability for Learning Systems, and we are looking for exceptional postdoctoral