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Field
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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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into tangible products. Critically, this work will generate a large open-source dataset of child-created games that can inform future designs of educational games and AI algorithms. The postdoctoral fellow will
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Strong background in communication theory, signal processing, and wireless communications, Extensive experience in physical (PHY) layer algorithm design and performance analysis, Proven track record
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that amplify human potential. The successful candidate will engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems
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in the design, implementation, and maintenance of data pipelines and leading/assisting in building algorithms for deep learning with close collaboration from the study team. While programming
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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
-scale data processing and analysis Preferred Qualifications, Competencies, and Experience Experience with implementation of coaddition algorithms and high-performance computing Experience with large
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
Experience with implementation of photometric and time-series detrending algorithms and high-performance computing Experience with large software projects, including proficiency across the software development
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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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