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programming, algorithm development and deep learning model implementation, and practical experience in drone and boat-based surveys are preferred. Background Investigation Statement: Prior to hiring, the final
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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, computer science, architecture, and engineering to develop scalable, data-informed solutions in sustainable design, construction, and energy management. The Cluster aims to modernize—and ultimately revolutionize
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Structures: the formal study of mathematical proof itself, as a subject in computational complexity, type theory, metamathematics, logic, and beyond. What is the space of mathematical truth, and what proofs
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unify programs and curricula in data science with an initial emphasis on questions grounded in data that are generated by human activity, including computational social science (e.g., algorithmic
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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computer science, statistics, operations research, or related computational fields. As part of an interdisciplinary research team dedicated to advancing management science, the fellows will develop novel
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 18 hours ago
Preferred Experience, Skills, Training/Education: 1. Ph.D. in Industrial Engineering, Biomedical Engineering, Data Science, Computer Science, or related fields. 2. The candidate is expected to have a strong
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, generative AI, NLP, or algorithmic decision systems Ideal applicants will have a strong background in operations research, statistics, or computer sciences and the ability to work across disciplinary