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functional data ”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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. This work involves developing novel techniques, algorithms, and software packages that enable more robust and scalable approaches to cybersecurity using AI-based techniques. In addition to technical
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to seek an optimal integration between the physical representations of the various processes and the computing power of the AI algorithms. Key duties Develop a robust framework to simulate streamflow
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
meteorology, and numerical modeling techniques with an understanding of local-scale physical and chemical processes from multiple emissions sources as represented in current models, and quantitative analysis
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
) strong communication skills – written and oral, c) ability to develop/translate model algorithms and develop new model code in Fortran, d) software skills needed to work with multiple observed and model
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position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
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scale and resolution. This ambitious project spans multiple institutes including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute, bringing
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Campus Open Date Oct 29, 2024 Description We are seeking multiple (3~4) highly motivated and collaborative Postdoctoral Research Associates with demonstrated skills in one or multiple areas
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
looking for a postdoctoral fellow interested in developing either machine learning algorithms for high-resolution histopathology imaging/spatial-profiling data in combination with other modalities (e.g
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this interdisciplinary project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures