17 machine-learning-"https:" "https:" "https:" positions at University of California Riverside in United States
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collaborative problem-solvers specializing in data science, statistical, and/or machine learning methods and tools, and have worked with various forms of data, including text. They should also enjoy conducting
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physical environments. This position focuses on research at the intersection of computer graphics, generative AI, and robotics, encompassing topics such as generative modeling, reinforcement learning, multi
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georeferenced data on pest outbreaks. The Scholar will use these data in collaboration with computer scientists to develop machine learning algorithms for the detection and management of biotic stress. The crops
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the aid of deep learning, machine, or other artificial learning technologies. Opportunities exist for collaborations with faculty in our department with a focus on plant pathogens and our faculty studying
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work in collaboration with the SOE Assoc. Deans for Undergrad and Grad Education, the Undergrad and Grad Academic Advisors, and Community Engaged Learning Coordinator to establish and maintain a Center
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Experience in developing and deploying chatbot applications. Knowledge of data privacy and security principles related to AI and machine learning Preferred Qualifications Familiarity with containerization and
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confidentiality at all times. Advanced computer knowledge with the ability to understand and learn new on-line programs. Demonstrated ability to work effectively in a service environment that is subject to frequent
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applying causal inference, spatial econometric modeling, and machine learning techniques to questions of regional economic development, urban sustainability, or entrepreneurship ecosystems. Proficiency in
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flexibility. Skills to learn organization-specific and other computer application programs. Basic skills to analyze and research information and learn to synthesize large amounts of data with strong attention
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sensitive information learned in the course of performing their duties. Sensitive information includes but is not limited to employee and student records, health and patient records, financial data, strategic