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Oak Ridge Institute for Science and Education (ORISE) participant, you will join a community of scientists and researchers developing interactive, Large Language Model (LLM) / Natural
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astrobiology. Description: There are various structures ranging from large-scale (such as coronal mass ejections and stream interaction regions) to small-scale (such as magnetic reconnections, ion beams, and ion
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projects gaining experience in image automation algorithms utilizing machine learning to enhance hemorrhagic shock resuscitation processing preparing large data sets for algorithm training learning computer
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. This project will focus primarily on the impact of large false data injection attacks (FDIA) on the physical layer operation of a maritime power electronics system. You will participate in validation and
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Health Agency (DHA) Public Health access and interact with critical data. By leveraging the power of large language models (LLMs), this system will translate user queries into executable code, eliminating
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to analyze and interpret large datasets, learning how to generate meaningful visual comparisons between simulated and observed data for model calibration and validation. These skills are essential
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to understand how the results of collected vapor samples will influence the system at large via optical, thermal, kinetic, and/or rate equation models. Why should I apply? Under the guidance of a
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qualifications: Strong data analysis skills, including experience working with large climate datasets. Programming experience, particularly in Python, and proficiency with Linux platforms. A proven record of
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in applied science sectors (e.g., Energy, Agriculture) The research will require analysis of large data sets in NASA high performance computing. Field of Science: Earth Science Advisors: Amal EL
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) to develop surveillance requirements and execute risk assessment of water, air, and soil in deployment environments. The Department of Defense (DoD) is focusing on future Large Scale Combat Operations with