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charge of data collection, cleaning, analysis and visualization; Co-instruct University 290 during each spring semester; Assist faculty director in reviewing applications for Galen mini-Magellan
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underrepresented communities, incorporating equitable and inclusive approaches to science engagement and decision-making processes. Technical Skills or Knowledge: Proficiency with data collection, analysis
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collecting data. Statistical skills, including data analysis and visualization. Familiarity with programming, including programming skills in R and/or Python. Preferred Qualifications Experience with or
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Experience Essential Qualifications: •Enrolled in a related Bachelor’s, Master’s, PhD, or Post-Doctorate degree program at UK •Required Dashboard Experience (PowerBi or Tableau) •Required Data analysis and
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National Institutes of Health (NIH) | National Institute of Technology, Tamil Nadu | India | about 1 month ago
intellectually curious scientist to join our team. The successful candidate will lead and contribute to innovative research projects involving large-scale genomic and multi-omic data analysis in
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preprocessing, postprocessing, automated testing, calibration, and visualization workflows; and conduct model verification, sensitivity analysis, calibration, validation, performance evaluation, and
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Mathjobs.org | about 1 month ago
scientific applications * Researching digital and post-digital computer architectures for science * Developing and advancing extreme-scale scientific data management, analysis, and visualization * Developing
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scientific applications * Researching digital and post-digital computer architectures for science * Developing and advancing extreme-scale scientific data management, analysis, and visualization * Developing
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Time 35 Job Duty Research Data Analysis and Scientific Computing. Analyze complex biological, environmental, genomic, computational, or physical datasets using advanced statistical and computational
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Time 35 Job Duty Research Data Analysis and Scientific Computing. Analyze complex biological, environmental, genomic, computational, or physical datasets using advanced statistical and computational