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well as machine 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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and metagenomic data. compile, manage, and analyze datasets with appropriate statistical methods including univariate and multivariate methods. lead preparation and publication of peer-reviewed
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interventions. Excellent command of advanced statistical methods, including longitudinal data analysis and complex multivariate analyses (e.g., structural equation modelling, SEM). Experience working
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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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-compatible hardware) Experience in conducting and analyzing cognitive neuroscience experiments Knowledge and skills in multivariate statistics and the measurement of change Familiarity with one or more of the
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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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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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skills in multivariate statistics and the measurement of change Familiarity with one or more of the following neuroimaging methods and modalities: functional connectivity, representational similarity