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times. Communicate insights effectively through reports, visualizations, and interactive platforms. Compile, process, and manage complex tabular, vector, and raster data sources in support of analyses and
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-Chem simulations for modeling aerosols and clouds in the Arctic region. - Analysis of the interactions between aerosols, clouds, and climate using data from the simulations. - Validation of the models
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to its Student Success team. This pivotal role is responsible for supporting data-driven decision-making through comprehensive data analysis, visualization, and organization, directly contributing to
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on funding) to assist with ecological research, quantitative data analysis, and manuscript development. Primary functions focus on supporting research projects spanning population modeling, habitat management
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preparation, participant observation, interviews, data analysis, and interpretation, in line with the project’s ethical approvals and research aims. 3. Document research output including analysis and
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directly with investigators in designing studies, selecting appropriate analytical methods, and preparing data and figures for publication. The incumbent also develops and maintains analysis pipelines and
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of the following: statistical modeling or machine learning, data visualization, SQL and relational databases, geospatial analysis, web scraping or APIs, and reproducible research workflows. Preference
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California State University, San Bernardino | San Bernardino, California | United States | 4 days ago
advanced AI/LLM technologies. The ideal student will have basic experience in the following: programming skills, AI/LLM models, and data analysis and visualization. Responsibilities include but not limited
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development. Conduct basic data analysis and prepare summaries, visualizations, and reports to support research activities. Maintain accurate records of data processing methods and ensure compliance with
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. Expertise in Power BI, data visualization, SQL, statistical analysis, and working with large or complex datasets will be highly valuable in supporting the university’s institutional research and data-driven