77 machine-learning "https:" "https:" "https:" "https:" "The Open University" 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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vitae (CV), and, optionally, up to three letters of reference. Applications must be submitted through AP Recruit at https://aprecruit.ucr.edu/JPF02201 . Full consideration will be given to applications
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information about the Department of Electrical and Computer Engineering, please visit https://engr.ucr.edu/ . Additional details regarding postdoctoral studies at UC Riverside can be found at https
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in physics or a related field. To apply: submit a CV, Cover Letter, Statement of Research, and a Statement of Teaching to https://aprecruit.ucr.edu/apply/JPF02178 . Review of applications will commence
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administration and maintenance knowledge and skills using permit and plan review software. Thorough knowledge of the principles and procedures of record keeping, and report preparation. Strong computer skills and
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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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aspects of student support and service delivery Additional Information Knowledge of common University-specific computer application programs and knowledge of University and departmental principles and
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of developmental advising and a knowledge of teaching and learning theory, the incumbent promotes student development and academic success to University Honors students by guiding them in making a successful