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techniques. By integrating Quantum Graph Neural Networks (QGNNs) and quantum-assisted neural networks with classical methods like Knowledge Graphs and Geometric Deep Learning (GDL), the study seeks to enhance
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the galaxy from their sources to the Earth. A developed Monte Carlo computer code is used to study the acceleration process by plasma shocks, while mathematical models have been designed to describe how
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theory into hands-on experience Network with world-class scientists Exchange ideas and skills with the Laboratory community Use state-of-the-art equipment Contribute to answers for today's pressing
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and prepare for readiness during operational tasks. The team is further exploring novel AI method developments, including applied mathematical and machine learning solutions for real-time use. Why
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scientific research and technological developments in diverse fields such as: applied mathematics, atmospheric characterization, simulation and human modeling, digital/optical signal processing, nanotechnology
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technological developments in diverse fields such as: applied mathematics, atmospheric characterization, simulation and human modeling, digital/optical signal processing, nanotechnology, material science and
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pursuing a degree or have a degree in a science, technology, engineering or mathematics (STEM) discipline, public policy, law or other fields that supports the DOE mission. Point of Contact Renee Eligibility
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providing the opportunity to participants to: Develop skills and knowledge in their field of study Engage with new areas of basic and applied research Transition classroom theory into hands-on experience
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. Qualifications The ideal candidate should have a strong background in the mathematical and computational aspects of modeling subsurface and surface flows. Knowledge in machine learning, data assimilation, and
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along the United States Mid-Atlantic and Northeast Atlantic Coast. Learning Objectives: The selected mentee will learn the theory behind and techniques to examine the resilience of tidal wetlands and