46 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" research jobs at Rutgers University in United States
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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 applied research and outreach
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analyses or the ability to effectively learn these techniques will be needed. Effective oral and written communication skills. Preferred Qualifications Experience in immunology, T cell biology, and cancer
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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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, computer vision and machine learning algorithms. · Information dissemination and decision-support services · Policy related analysis and investigation · Previous interactions with transportation funding
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with laboratory management. Updating and maintaining data files and associated computer software. Performing animal husbandry duties. Training and overseeing undergraduate students working in
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maintaining and fostering a safe, diverse, and respectful workplace environment, creating employment opportunities for our nation’s military veterans, and ensuring accessibility and accommodation
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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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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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learn, work, and serve the public at Rutgers locations across New Jersey and around the world. Posting Summary Rutgers, The State University of New Jersey has opening for two (2) Postdoctoral Associates
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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