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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
of Computer Science at the University of North Carolina at Chapel Hill seeks a talented, highly motivated postdoctoral researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is
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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal
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benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu/benefits/ Duke is an Equal Opportunity Employer committed to providing
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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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of programming or scripting languages such as Python, Fortran, R or others. Experience in remote sensing data analysis and geographic information systems. Experience in machine learning motivated algorithms and
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the Electrical Engineering department, and Daning Huang in the Aerospace Engineering department in the area of Scientific Machine Learning. The project is to develop computationally efficient reduced-order
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communication theory, machine learning, complex networks, and optimization. The employment This employment is a temporary contract of two years with the possibility of extension up to a total maximum of three
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for this position will work as a member of an interdisciplinary team on research involving the use of statistical and machine learning methods for the development of Immune Digital Twins. There will be potential
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ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track record in conducting machine learning research