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Field
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analysis of non-invasive brain stimulation data. Proficiency in statistical analyses of multivariate data sets. About the Department To learn more about the Department of Neurology, please visit https
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of multivariate techniques; repeated measures designs; path analysis, discriminant and factor analyses; and structural equation modeling. Knowledge of quantitative genetic approaches such as genome-wide association
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, differential abundance testing, community composition comparisons, and other multivariate statistical approaches used to evaluate associations among bacteriophage populations, bacterial communities, clinical
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Familiarity with brain imaging analysis acquisition Knowledge of multivariate statistics and/or digital signal processing Proficiency in Python. Parallel computing processing experience is highly appreciated
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experience in ecological field research and data analysis. Strong quantitative and analytical skills, including experience with ecological modelling and multivariate data analysis. Proven ability to work
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with fungal community, genomic or transcriptomic analyses Knowledge of multivariate analyses and statistical modelling Excellent communication skills in written and spoken English We consider it a merit
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learning and multivariate decoding of neuroimaging data to predict subjective experiences and individual differences. Successful candidates will be supported in building a research program at the
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experimental procedures, review of data for quality control, supervision of data entry/data analysis, analysis of research hypothesis using descriptive and multivariate statistics, and the development
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of the Autism Diagnostic Observation Schedule-2 (ADOS-2). Experience performing advanced statistical modeling and analysis with longitudinal and multivariate datasets, including multi-level modeling (MLM
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laboratory staff, review of data for quality control, supervision of data entry/data analysis, analysis of research hypothesis using descriptive and multivariate statistics, and the development of independent