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in upland gamebird research to lead our Gamebird Research Station program. The successful candidate will work with the team of gamebird staff and students from the Lyon Center to contribute knowledge
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: Professional Staff Job Description Summary: The Postdoctoral Fellow will support the Community Health Improvement Program for Individuals with Intellectual Disabilities (CHIP-ID), a research initiative within
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presentations for both internal and external meetings. Hands-on experience in GPCR signaling assays, electrophysiology assays and in-vitro/in vivo ADME/PK evaluation and computational drug discovery will be a
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California Class A driver's license, have a driving record that is in accordance with local policies/procedures, and/or enroll in the California Employer Pull Notice Program Undergraduate degree (BA/BS
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to support the nourishment and well-being of all people; sustain our nation’s agroecosystems and natural resources; and ensure the economic competitiveness and excellence of our agriculture. The vision
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
that the University of North Carolina at Chapel Hill strives to instill in every unit, department, and program at this great University. The Graduate School supports graduate students in almost every program across
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is in accordance with local policies/procedures, and/or enroll in the California Employer Pull Notice Program Undergraduate degree (BA/BS) or equivalent experience. Experience working in field research
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factors. Though not required, we are particularly interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and
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point AC3 – Research and laboratory experience in: AI and Computer Vision applied to complex problems; Autonomous systems and robotics, including drones applied to urban mobility; Data analysis
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the group's research on developing novel machine learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image