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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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postdoc candidate, with a keen interest in academic and professional development, who meets the following requirements: a PhD degree in computer science or artificial intelligence; demonstrable machine
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
desirable. Candidates with experience in time-series machine learning, advanced data analytics, and programming (Python) are especially encouraged to apply. Special Physical/Mental Requirements Special
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relevant subject area: Machine Learning, NLP, Computer Vision or related fields. Strong publication record in AI/ML/CV or related areas. Ability to work independently and collaborate across disciplines
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together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for multimodal federated learning
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with the world's first exascale system, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate
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throughout their evolution. Our vision combines ideas from differential geometry, numerical analysis, scientific computing, dynamical systems, and applied mathematics to develop new mathematical frameworks
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; developing novel ways to combine quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 27 days ago
involves repetitive bench tasks such as pipetting, extended periods standing or seated at a laboratory bench, and extended periods at a computer workstation for data analysis. Reasonable accommodations will
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; developing novel ways to combine quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational