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experience working with large complex longitudinal datasets is required. (Experience conducting statistical analyses such as robust variance, binomial regression, generalized estimating equations, Cox
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an understanding of the world’s complex, interlocking systems. We believe that access to nutritious food and a healthy environment is a fundamental human right. We believe that ensuring a prosperous global future
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experience working with large complex longitudinal datasets is required. (Experience conducting statistical analyses such as robust variance, binomial regression, generalized estimating equations, Cox
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Intelligence (AI) and Machine Learning (ML) methods to tackle complex biomedical challenges in nutrition and health. This is a one-year full-time benefits-eligible position that may be extended for up to four
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to tackle complex biomedical challenges in nutrition and health. This is a one-year full-time benefits-eligible position that may be extended for up to four more years, depending on performance, continuation
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an understanding of the world's complex, interlocking systems. We believe that access to nutritious food and a healthy environment is a fundamental human right. We believe that ensuring a prosperous global future
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experience working with large complex longitudinal datasets is required. (Experience conducting statistical analyses such as robust variance, binomial regression, generalized estimating equations, Cox
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researchers to advance Systems Science and Engineering by modeling human behavior in complex dynamic networks addressing global challenges. Emphasizing Cyber-Human-Physical Systems, it tackles issues like
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breakthroughs requires an understanding of the world’s complex, interlocking systems. We believe that access to nutritious food and a healthy environment is a fundamental human right. We believe that ensuring a
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the answers we seek focus on three overlapping concerns: We believe that achieving next-generation scientific breakthroughs requires an understanding of the world’s complex, interlocking systems. We