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of the Adaptive Hydraulics (AdH) framework, as well as advancing high-fidelity computational fluid dynamics (CFD) methods for free-surface and multiphase flow simulations. Activities may include improving and
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wearables. Experience in experimental design and analytical characterization is necessary. Working knowledge of data analysis and analytical methods including spectroscopy and microscopy is preferred. Primary
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, learning of data collection techniques, and methods for data assessment and presentation Gain first-hand knowledge of Forest Service Research & Development science and National Forest System management
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and accurate orbit determination and hazard assessment methods. Research will center on: (1) developing new observation weighting schemes that exploit the expanded metadata available in the Astrometry
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intelligence agencies through applied research and development. What will I be doing? This project involves the development of extraction and instrumental methods for the analysis of residues from detonators
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reduction techniques and numerical methods for subsurface and surface flow processes. You will gain experience with forward hydrodynamic models developed in the Coastal Hydraulics Laboratory and contribute
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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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, you will join a community of scientists and researchers in an effort to explore security implications in trusted and secure systems at the application, hardware, firmware, and software levels
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wildland-urban interfaces— across a wide range of climate conditions. Using machine learning methods, we will optimize the weightings of each contributing factor and identify the key drivers of wildfire risk
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sciences, Geology, or closely related field). Degree must have been received within the past four years. Preferred skills: Experience with Microsoft Office products. Experience using geospatial software