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of Insurance (DOI) and the Center for Health Information and Analysis (CHIA) Researching public policy topics, including conducting literature reviews on health policy, public health, and behavioral health
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security, and prevention of adversarial attacks. Data Science: Strong understanding of data structures, algorithms, statistical analysis, and data visualization techniques relevant to AI applications. KEY
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. Experience with data visualization or simple dashboard tools. Familiarity with UI/UX tools (e.g., Figma) or basic design principles. [SPRINT Internship | Word]. Prior participation in team-based academic
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, coordinates, and/or assists with proposal writing to develop additional funding. 4. May oversee and/or coordinate the collection, compilation, and analysis of program activity data; develops, writes, and
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-solving frequently requires analysis of unique issues/ problems without precedent and / or structure. May manage programs that include formulating strategies and administering policies, processes, and
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, programming, and documentation skills. Demonstrated experience in data analysis and system configuration. Proficient with web-based applications and programming tools. Ability to learn new skills quickly
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Contact details of two referees (see also the list of documents required - the attached file) Website for additional job details https://praca.bip.uj.edu.pl/documents/145868730/160095348/Information
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
the course of the projects. Examples of Past Projects: IMPAN analysis; feasibility studies; Data visualization; Forestry and farm management plans; Manufacturing process improvement; Creating financial models
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and/or R (geospatial stacks, data wrangling, visualization). Record of peer-reviewed publications commensurate with career stage and strong scientific writing skills. Ability to work collaboratively
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, including experience with data manipulation, statistical analysis, and data visualization tools; Usage of Machine Learning and Deep Learning libraries (e.g., Pytorch, Tensorflow) will be considered a