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Field
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Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your
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architecture of entirely new foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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, battery technology, aerospace, water systems and sustainable energy. Learn more at unr.edu/engineering Exempt Yes Full-Time Equivalent 100.0% Required Attachment(s) Please note, once you submit your
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machine learning algorithms to support the traceability of the beef’s geographical origin. She/he will participate in all stages of the project, including planning and supervision of sample collection and
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SPECIFICS Postdoctoral Scholar (Machine Learning or Artificial Intelligence in Molecular and Cellular Biology) The National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 20 hours ago
of Yuhua Duan. This project will be hosted at the NETL Pittsburgh, PA campus. Although material modeling with artificial Intelligence/machine learning (AI/ML) applications and experimental instrumental
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, air quality, and health. We seek a PhD or Postdoc to work on either of the two topics: Autonomous reaction discovery: combining quantum chemistry, machine learning, and automation to chart oxidation
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: Within this international project, TU Delft will develop a machine learning-based forward operator to enable the assimilation of SAR imagery into the crop growth model. You will: Process SAR imagery over
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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission