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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic
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Essential Qualifications Applicants require a PhD in a Biochemistry-related field Preferred Qualifications: Experience with animal behavioral studies, advanced statistics, and experimenta design
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Record of scholarly publication Strong quantitative analysis skills, with a minimum of 3 years of statistical programming experience with R, Stata, and/or SAS Excellent English language written, verbal
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of Health R01 DC017114. The goals of this grant are to understand the time course of listening effort, especially as it relates to listening with a cochlear implant. The PA is expected to focus on statistical
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or more of the following: ● Experience with urban watershed modeling or lake systems modeling ● Experience with limnological or aquatic field methods ● Experience with statistical methods for making
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
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classes in the graduate and undergraduate curricula and/or similar classes, either in an in-person or online modality: ● Quantitative and Psychometric Methods ● Multivariate Statistics ● Measurement
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Preferred Qualifications: • Demonstrated productivity through first-author and collaborative publications in immunology • Strong background in experimental design, statistical data analysis, and data
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statistical methods to agronomic research, including mixed models, geospatial statistics, multivariate analysis, and machine learning - Must possess and maintain an active and valid driver’s license Preferred
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internet connection for duties undertaken remotely. Qualifications Required Qualifications: A PhD degree in Biostatistics, Statistics, Computer Science or a related field who possess STRONG computing