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Cornell University, School of Chemical and Biomolecular Engineering Position ID: Cornell-ChemE-POSTDOC [#30598, WDR-00055411] Position Title: Position Type: Postdoctoral Position Location: Ithaca
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
and lifelong learning and enjoy exclusive perks for numerous retail, restaurant and performing arts discounts, savings on local child care centers and special rates on select campus events. UNC-Chapel
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/Scientist IV, Electrical and Computer Engineering Posting Number req25245 Department Electrical and Computer Engr Department Website Link https://ece.engineering.arizona.edu/ Location Tucson Campus Address
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demonstrable background in machine learning including published work. Must have demonstrable experience in building AI models for directed evolution of proteins and protein function prediction and optimization
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, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu/benefits/ Duke is an Equal Opportunity Employer committed
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outputs, and other scholarly measures of impact. Strong demonstrable background in machine learning including published work. Must have demonstrable experience in building AI models for directed evolution
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dossiers; organize faculty and postdoc searches. Faculty Support â“ Provide support for faculty regarding scheduling, travel, and administrative office support; arrange and support faculty meetings. General
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and engineers. Key Responsibilities 1. AI Model Development & Testing Assist in developing machine learning and deep learning models for medical imaging analysis. Implement and fine-tune models using
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The Daasbjerg research group at the Department of Chemistry, Aarhus University, is seeking a candidate for a 31-month postdoctoral position. This position focuses on AI/machine learning to develop a
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work closely with I-CREWS researchers across the state. The position emphasizes developing, integrating, and applying modeling approaches—including machine learning (ML), hydrologic and energy systems