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scoping to deployment and monitoring of production-grade models—with a focus on both Generative AI and Deep Learning. The ideal candidate holds a Ph.D. in Deep Learning or Generative AI and brings a strong
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Operations, Storrs Campus Salary Range: $66,517.00-$85,519.00 Yearly. Individuals new to state service start at the minimum of the pay plan. Link to Water Pollution Control Operator Job Specification: https
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learning and deep learning models for renewable energy forecasting, particularly wind power generation. Working with data-driven weather prediction models and high-resolution meteorological datasets
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, multimodal foundation models, continuous learning systems, or agentic AI models. Experience with state-of-the-art multimodal foundation models and agentic AI frameworks Experience in large-scale deep learning
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 21 days ago
Deep Learning), successful experimental collaboration experiences and excellent communication skills are preferred. Create a Job Match for Similar Jobs About The University of North Carolina at Chapel
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of, or willingness to learn, the complexities of the University environment, including the differing governance and risk considerations for research and enterprise data. Foundational knowledge of cyber security
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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. Ouyang is a physician-scientist and cardiologist with subspecialty expertise in non-invasive imaging and technical background in programming, statistics, and deep learning. As a statistician by training
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of the nation’s oldest living-learning programs for first-year students where faculty and Student Life efforts are integrated in meaningful ways. As a residential campus, the living-learning experience is a
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, KELIM score), mutational profiles, histopathological information, and long-term survival outcomes. The first objective is to implement automated deep-learning–based segmentation of primary ovarian tumors