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or reporting outputs for internal or external audiences. Additional Qualifications and Skills: Experience using data analysis and visualization tools such as R, Python, SQL, Stata, or Tableau. Familiarity with
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Machine Learning Engineer (MLE) / Data Scientist (DS) to support the end-to-end management, analysis, and visualization of behavioral and clinical data streams. The full-stack MLE/DS will work on studies
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software platforms. · Build and maintain robust data analysis pipelines for large-scale electrophysiological and imaging datasets, including spike sorting, network analysis, and state/dynamics
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seeking to hire a Full-Stack Machine Learning Engineer (MLE) / Data Scientist (DS) to support the end-to-end management, analysis, and visualization of behavioral and clinical data streams. The full-stack
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bioinformatics analysis pipelines for processing RNA-seq, single-cell RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages
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our self-service Analytic Data Discovery portfolio (QlikView). Key Responsibilities: Data Analysis & Strategic Reporting Analyze & Synthesize: Conduct complex quantitative analyses to identify workforce
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), library research (Pubmed searches, systemic review methods), and statistical analysis (data visualization, descriptive analyses, time series analyses, latent modelling, multilevel modelling); Project
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control and automation using LabVIEW, as well as data and image analysis. The position also includes general laboratory support, such as preparing reagents and solutions, organizing and maintaining
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-service Analytic Data Discovery portfolio (QlikView). Key Responsibilities: Data Analysis & Strategic Reporting Analyze & Synthesize: Conduct complex quantitative analyses to identify workforce trends—in
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the PI and other team members to perform statistical analyses using R for manuscripts and grants, create data visualizations (tables, graphs, figures, etc.), and assist in the writing of scientific results