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studies. Strong statistical skills in causal inference and the ability to manage various sources of bias are essential. The ideal candidate will also have experience in both aging and environmental
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large cohort studies. Strong statistical skills in causal inference and the ability to manage various sources of bias are essential. The ideal candidate will also have experience in both aging and
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informatics, medical imaging analysis, AI/ML development, omics technology development, biomedical data integration and mining, translational bioinformatics, computational medicine, statistics/biostatistics
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imaging analysis, AI/ML development, omics technology development, biomedical data integration and mining, translational bioinformatics, computational medicine, statistics/biostatistics, mathematics, data
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datasets. Conducting extensive independent statistical and spatial analyses to support research objectives. Drafting grant proposals and contributing to the development of new research proposals
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, statistical genetics, cost-effectiveness research, clinical trials, and high-dimensional data analysis) are encouraged to apply. We welcome applications from scientists with a strong background in Epidemiology
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to applicants with in-depth data processing and statistical expertise (e.g., experience with R software, data aggregation, and multi-level mixed effects modeling). Required Application Materials Applicants should
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and Engineering (CSE), Statistics and Probability (STT), and Counseling, Educational Psychology, and Special Education (CEPSE) to identify a tenure system scholar in postsecondary Computing Education
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desirable. Preference will be given to applicants with in-depth data processing and statistical expertise (e.g., experience with R software, data aggregation, and multi-level mixed effects modeling). Required
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, gamma spectroscopy, alpha spectroscopy, and liquid scintillation counting. Skillful ability to analyze data using software or tools such as Excel, statistical software, or chromatography data systems