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multivariate analysis. Acts as a subject matter expert on research methods and equipment functions. May instruct an academic section in research techniques, instruments, methods, and procedures. Perform other
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experience in genetic manipulation of microorganisms Competences and experience in advanced statistics (e.g., multivariate statistics, GLMs) and programming (e.g., python, R) Publication(s) from earlier
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experimental design, modelling, programming, or multivariate data analysis, experience in process development and pilot-scale trials involving membrane and/or food processing technologies, experience
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University of California, Los Angeles | Los Angeles, California | United States | about 11 hours ago
must have strong foundation in statistics, including multivariate statistical analysis and appropriate validation of quantitative models. The candidate must have experience working in Linux or Unix-based
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for the characterization of food, protein, or colloidal systems, knowledge and experience in statistical experimental design, modelling, programming, or multivariate data analysis, experience in process development and
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, dimension reduction, pathway analysis, survival analysis, and multivariable modeling. Strong analytical, organizational, and problem-solving skills. Ability to work independently while contributing
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 3 months ago
the life sciences Expertise with a wide range of modern statistical modelling and multivariate analysis methods Sound experience with statistical software (preferably R) Fluency in both written and spoken
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of quantitative genetics, linear models, and multivariate statistics. The candidate should demonstrate a proven record of effectively working in teams and mentoring students. Abilities with bioinformatic analysis
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equations, numerical analysis, mathematicalmodels in biomedicine, biostatistics, machine learning, statistical learning, multivariate statistics, time series,mathematical modelling, generalized linear models
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rejection, source localisation, time-frequency decomposition, and multivariate pattern analysis. Develop and apply quantitative analysis pipelines in MATLAB, incorporating dimensionality reduction (PCA, UMAP