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Number: 6799776 Anatomy Learning Institute - Adjunct Pool (2025-26) Posting Number: R0004158 Location: Balboa Campus - San Diego, CA PLNU is a Christian liberal arts university in the evangelical, Wesleyan
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University of California, San Francisco | San Francisco, California | United States | about 5 hours ago
about where a new hire would be placed on the range. To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation
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experiences of teaching and/or supervision of students' project work, knowledge in machine learning and deep learning, language technology, industrial economics, as well as completed third-cycle (doctoral
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present them at major international conferences. Experience has shown that applying deep diagnostic and operational expertise provides strong synergistic benefits and accelerates scientific progress
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of their work in refereed journals and present them at major international conferences. Experience has shown that applying deep diagnostic and operational expertise provides strong synergistic benefits and
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development of Northern Ireland. Our core business activities are teaching and learning, widening access to education, research and innovation, and technology and knowledge transfer. - THE ROLE - The role
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) Develop AI‑driven model calibration by designing a deep‑learning pipeline mapping data extracted from experiments onto force fields and use these predictions to initialise Cytosim simulations. (3) Use
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Job Description For over 160 years, the University of Washington has been a hub for learning, innovation, problem solving and community building. Supporting this legacy and important public mission
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Teaching & Learning, web developers, faculty and staff responsible for digital content. Required Qualifications: Bachelors degree in Computer Science, Information Technology, or an equivalent combination
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methodologies, including machine learning, deep learning, TinyML, federated learning, explainable AI (XAI), digital twins, and other emerging techniques relevant to the RGs. Support interdisciplinary research