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align with the program’s streams: (i) artificial intelligence and machine learning; (iii) applied data science (big data analytics, databases, data mining, etc.); (iii) cybersecurity. The selected
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leadership roles within large, interdisciplinary projects. Understand and personally champion equity, diversity and inclusion through the development of research relevant to marginalized communities, and the
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. Qualifications: A doctoral degree in epidemiology Knowledge of advanced epidemiologic methods Strong data manipulation and analytic skills using statistical programming software, e.g., SAS Demonstrated ability
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procedures Participate in the analysis of university-wide records requirements including compliance, information management and organizational and operational impact Analyze overall effectiveness with respect
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participating in the collaborative development of: (1) spatially explicit baseline data of cropping practices, including identification of representative crop rotations, and (2) spatially explicit baseline
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focusing on computational integration of large-scale functional and comparative multi-omic datasets, tool development and AI approaches are especially encouraged to apply. The successful candidate will be