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Plotly, Dash, and R Shiny to translate complex data into clear, actionable visual analytics and dashboards. Learning Objectives: Throughout the fellowship, you will engage in structured learning
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methods, experimental design, and data quality Comfort using spreadsheets or other tools for organizing and visualizing information Strong attention to detail when documenting observations and following
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) Strong skills in visualizing and interpreting epidemiological data and model outputs for diverse audiences Proficiency using Git/GitHub in a collaborative programming environment (branching, pull requests
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pests and disease in greenhouses and research orchard blocks. Data Management: Meticulous record keeping of experimental data and notes; digitizing data; basic data visualization and statistical analyses
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, and analysis of DPS partner investment data. Collaborate on the development and expansion of a dashboard to collect, store, visualize, and analyze DPS science and evaluation science data. Learning
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methods to clean large line-level datasets, append and validate geospatial data, and create impactful visualizations, based on program needs and resources Describe knowledge gaps between theoretical and
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the BioPermit information technology system and electronic database. Build skills in data management, analysis, and visualization of trends related to infectious biological-agent importation. Gain exposure
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phylogenetic analysis; Automate the production of tables, figures, visualizations, and quality-control summaries; Integrate genomic, laboratory, and epidemiologic data from multiple sources; Train to develop
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complete application consists of: An application Transcripts – Click here for detailed information about acceptable transcripts A current resume/CV, including academic history, employment history, relevant
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reproducible analytic workflows, integrating data from multiple sources, creating data visualizations, and contributing to scientific reports, presentations, and manuscripts. This fellowship will provide a