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experiential learning courses, as well as contributing lectures to core plant pathology courses that support required and elective curricula in the Undergraduate Program in Plant Science and Graduate Program in
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virtual reality development, machine learning, or advanced data analyses and modeling are highly desirable. Position Status Full Time Posting Number 25FA0682 Posting Open Date Posting Close Date
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to oversee research activities outlined in NSF Grant 2520154 “Understanding Expectation-Driven Learning in Early Childhood: An Experimental and Computational Investigation,” under the supervision of Dr. Kimele
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Knowledge, Skills, and Abilities Computer literate, with comfort navigating file systems, performing basic troubleshooting, and learning command-line workflows (PowerShell and/or Python). Ability to work both
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undergraduates in scientific research projects. ESSENTIAL DUTIES & RESPONSIBILITIES INCLUDE: 1) Computer simulations of protein structure and computational protein design of small peptides and proteins. 2
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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and
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opportunities for experiential learning on and off campus, including a growing emphasis on international experiences through short- and long-term study abroad. Students also have access to a robust program of
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, computer science, or a related field. Expertise in causal inference and machine learning (in particular reinforcement learning), and strong experience with programming are desired.. Excellent communication and
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, computer science, or a related field. Expertise in causal inference and machine learning (in particular reinforcement learning), and strong experience with programming are desired.. Excellent communication and
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use of laboratory equipment, including vibratome, scales, stirrers, pH meter, and knows or will learn any and all equipment, software, and specialized materials needed to support the effective and