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-world problems in the fields of Biology, Health, and Engineering. An effective research program will execute use-inspired discovery with an entrepreneurial mindset that develops science and solutions
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on developing and analyzing algorithms, building reproducible computational studies, and disseminating results in leading venues. The position collaborates with faculty, students, and external partners
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to this classification. It is not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. Summary: The Goodwill Computing Lab seeks a Postdoctoral
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to this classification. It is not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. Summary: The Goodwill Computing Lab seeks a Postdoctoral
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of statistical physics, information theory, and computational modeling. RESPONSIBILITIES The Postdoctoral Research Associate will perform basic or applied research of a limited scope, primarily using existing
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to this classification. It is not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. Summary: The Goodwill Computing Lab seeks a Postdoctoral
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proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. ● Pursue research topics such as protecting
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, that will work halftime with the NU Public Evaluation Lab (NU-PEL) on the evaluation of the Boston Area Youth Direct Cash Transfer (BAY-CASH) program and half-time with Dr. Jonathan Zaff on a research
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of statistical physics, information theory, and computational modeling. RESPONSIBILITIES The Postdoctoral Research Associate will perform basic or applied research of a limited scope, primarily using existing
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global and societal needs. Our broad mix of experience-based education programs?our signature cooperative education program, as well as student research, service learning, and global learning?build