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Field
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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Center’s mission is to create the theoretical, computational and algorithmic paradigms that will enable us to understand the programs of life and how they connect across scales, from proteins to cells
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verification algorithms and prototypes on large microgrids, Naval systems, and utility systems. ● Assist grant proposal writing, work collaboratively with industry and government, and mentor graduate
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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lattice models. We welcome applications of candidates from a wide range of backgrounds from theoretical physics to pure mathematics. Candidates with experience in tensor network algorithms, rigorous
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computing, and digital twin technologies for mission autonomy and predictive analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission
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Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods of research, testing and data
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computing algorithm to implement the modelling of inelastic molecular collisions on present-day quantum computing hardware (e.g., IBM-Q, IonQ) within a framework of mixed quantum/classical theory
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for diagnosis and prognosis of different sarcomas. He/she will develop and train deep learning models with state-of-the-art algorithms based on histology whole slide images. They may also contribute to research
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, and medicine. Key Responsibilities Collaborate with researchers to design, develop, and refine large language and generative models. Develop novel algorithms for generative modeling tasks and optimize