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, facilitating rapid data acquisition. Statistical Analysis: Analyze data using practical and easily applicable statistical models, with a primary focus on linear regression (LR), to evaluate calibration accuracy
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on critical issues of food production and sustainable agroecology. Summary of Duties: Recruitment for a post-MS or post-PhD candidate with experience in research, statistical analyses, writing, and publishing
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formulation, benchmarking, and policy development. This includes using mathematical and statistical techniques, developing predictive models to forecast future outcomes, synthesizing data, and/or creating
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, and statistical methods. All candidates must demonstrate strong commitment to teaching and service. Required Qualifications: Ph.D. in Data Science, Data Analytics, Statistics, Computational Mathematics
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systems. Demonstrated experience with data management and visualization techniques, and/or statistical analysis and predictive modeling. Preferred Qualifications: A master's or doctoral degree. Working
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management systems. Demonstrated experience with data management and visualization techniques, and/or statistical analysis and predictive modeling. Preferred Qualifications: A master’s or doctoral degree
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conditions. Experience with applied plant pathology in field and greenhouse environments. Ability to design statistically valid research trials, and proficiency in analyzing and interpreting data effectively
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, produce multiple Maintenance Reports, and keeps Maintenance department statistics. The Work Schedule: Sunday – 12am-6am; 6pm-11pm Friday 11pm- Saturday 6am Saturday – 6pm-12am Required Qualifications: High
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, statistics, or closely allied field OR additional qualifying experience may be substituted, year for year, for the required education. AND One year of experience in negotiating, administering, or terminating
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interpret experimental data using relevant statistical analyses and computer software (including SAS or R). Develop graphs and tables for research publications using relevant computer software (including