34 machine-learning Postdoctoral research jobs at Rutgers University in UNITED-STATES
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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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Movement Sciences at Rutgers University is seeking a highly motivated Post Doctoral Associate to work on translational projects at the intersection of biomechanics, machine learning, exergaming, and mobile
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the application of 1) Structural Health Monitoring (SHM) and Weigh-In-Motion (WIM) systems integrated with advanced probabilistic methods, machine learning and Artificial Intelligence (AI) approaches, and 2
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environment. Highly motivated, passionate about science, a strong communicator, and possess an internal drive to learn independently. Equipment Utilized Physical Demands and Work Environment Overview While New
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and experience using geographic information systems software are also required. Knowledge of Git is a plus. The successful candidate must be willing to learn new methods as needed and have the ability
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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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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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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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well as leading efforts in mutual learning among researchers, practitioners, advocates, community organizers, and policymakers. The Associate will conduct research in the context of research practice partnerships
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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