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/Qualifications - Demonstrated expertise in advanced statistical techniques, such as: Multilevel modeling (HLM, mixed-effects models) Longitudinal and panel data analysis Structural equation modeling (SEM) Causal
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-experiments for research purposes, Knowledge of online experiment, task and/or survey platforms (e.g. Gorilla, Prolific, etc.), Awareness of time-series, multilevel, Bayesian, or causal inference analysis
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, including descriptive, correlational, factorial, regression, and multilevel analyses, as well as qualitative data analysis. Preparing summaries, technical reports, and scientific publications based on project
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, multilevel modelling, and other key epidemiological analyses. (Required) Skill in conducting literature searches. (Required) Ability to work independently, under tight deadlines. (Required) Ability to interact
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focus on quantitative methods Excellent skills in quantitative methods. Expertise with panel data analysis, multilevel models and/or causal inference is an advantage Interest in one or more of the
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, linear mixed models, structural equation modeling, multilevel models) You are proficient in using one or more common statistical analysis software packages (R, SPSS, Mplus, Python, etc.) You have a very
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of new grant proposals, including contributing to specific aims, research strategies, and budget justifications. Data Analysis and Dissemination Support advanced quantitative analyses (e.g., multilevel
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Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences (formerly Institute of Genetics and Animal Biotechnology PAS) | Poland | about 1 month ago
, molecular biology, genomics, and in vitro research, providing a comprehensive, multilevel framework for investigating the interactions between iron and lipid metabolism. Discipline: animal science and
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complex longitudinal multi-site data and requires familiarity with statistical programming and advanced epidemiological regression methods such as survival analysis and multilevel models. Using a wide
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
multiple sources. * Familiarity with Medicare Cost Report Data * Some exposure to methods beyond standard regression (e.g., panel/longitudinal data or multilevel modeling) is a plus, but not required