21 Statistics positions at Michigan State University in United-States in United States
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collected in research projects, including quality assurance, scoring of instruments, merging and transformations of data sets for statistical analyses; conducting analyses of data from clinical trials and
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of instruments, merging and transformations of data sets for statistical analyses; conducting analyses of data from clinical trials and observational studies, including health insurance claims data; preparation
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, Statistics, Economics or Research Methodology; three to five years of related and progressively more responsible or expansive work experience in research design, statistical methods and knowledge of computer
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/Experience/Skills Knowledge equivalent to that which normally would be acquired by completing one or two years of post-bachelor degree work, such as a Master's in Educational Administration, Statistics
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, implementation, data management, statistical analysis, and dissemination of primary care research for the Collaborative. This individual will collaborate with primary care practices, including the Family Medicine
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. - Analyze data using statistical methods and present it at group meetings. - Collaborate with lab members on the project and discuss experimental plans. - Present data at weekly lab meeting. - Meet biweekly
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of the research associate may include, but are not limited to: Leading the writing and preparation of manuscripts for peer-reviewed publication Designing and implementing inferential statistics pipelines to analyze
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/access, and the application of statistical and econometric methods to transportation data. The successful applicant will lead day-to-day activities on various research projects funded by public and private
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, gene expression analysis, etc. Skill and experience of working in the greenhouse and field for the evaluation of soybean biological traits independently. Skill in experimental design, statistical
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scripts. • Writing documentation on existing SQL/Python scripts and newly created scripts. • Creating predictive statistical models (including neural network and tree-based logic models) using large