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Field
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-Yale collaborators, pharmaceutical companies, HIC, IRB and funding sources. 9. Performs descriptive and multivariate statistical analyses of data, using computer software. 10. Designs and implements
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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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methods Experience with advanced statistical methods (e.g., multivariate regression, latent class/profile analysis, structural equation modeling, factor analysis, canonical correlation analysis) Prior peer
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Complexity» (NewPC). About the project/work tasks The project aims to develop multivariate algorithmic and complexity tools for optimization problems involving geometric and algebraic objects such as points
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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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in Communities (ARIC) study (https://sites.cscc.unc.edu/aric/ ). ARIC is a large-scale prospective epidemiologic cohort which is evaluating associations of mid-life risk factors to risk of
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research experience. Advanced Epidemiological & Statistical Analysis: Proficiency or advanced training in applying complex epidemiological methods, linear/non-linear modeling, or multivariate survival
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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
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candidate at the University of Primorska – PhD study program in Computer Science. It is expected that the researcher will contribute to the projects ERC ARCHI-SKIN, GA #101044468 https://archiskinproject.eu