26 machine-learning "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" positions at Zintellect
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development to support extended reality technologies, machine learning pipeline integration, integration of sensors/devices to mobile platforms, and creating novel clinical decision support applications for our
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project), create a unique opportunity to apply machine learning and neural network methodologies, in conjunction with simplified ice sheet models, to advance understanding of ice sheet basal processes and
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Instrument for Magnetic Sounding (PIMS) on the Europa Clipper Mission. Space Sci Rev 219, 62 (2023). https://doi.org/10.1007/s11214-023-01002-9 3. Kataoka, R., Nakano, S. & Fujita, S. Machine learning emulator
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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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Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign Nationals eligible for an Exchange Visitor
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that are facile with computationally efficient, rigorous machine learning for image region identification, demonstrate an understanding of both planetary and scalable computer science, and have publication
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, Computer Science, Software Engineering or other eligible discipline. U.S. military veterans who have been honorably discharged (or who have been medically discharged because of a service-connected
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, or other eligible discipline. Degree must have been received within five years of the appointment start date. U.S. military veterans who have been honorably discharged (or who have been medically
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Organization U.S. Department of Defense (DOD) Reference Code USAISR-2026-0005 How to Apply Click on Apply at the bottom of the opportunity to start your application. Description The U.S. Army
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at https://ntl.bts.gov/ntl. Are you interested in learning how to develop a new archival repository into a more discoverable, rich resource for the Department of Transportation? Here is an opportunity