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datasets are preferred. The Postdoctoral Associate will contribute to advanced statistical analyses, geospatial analysis, and data visualization, as well as to the development and dissemination of findings
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
across the team to find creative solutions and deliver them. * Skilled at data visualization and presentation: The candidate will be called upon to present work at national and international research
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large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these skills Excellent written and communication skills, including scientific
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sequencing and other NGS-based data from patients, including mutation calling and detection of mosaic mutations. The work may also include statistical analyses and data visualization to identify and
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with: Experience with web-GIS development or geospatial data visualization. Experience with high-performance computing clusters or cloud-based Earth observation platforms (e.g., GEE Python API
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. Certifications/Licenses Required Knowledge, Skills, and Abilities Proficiency in statistical programming (e.g., R, Python) for data analysis and visualization. Strong analytical, organizational, and time
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investigators, research collaborators, graduate students, and visiting scientists to support ongoing research activities and project deliverables. Assist with model setup, data processing, analysis, visualization
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learning models for emission predictions Participate in field campaigns across Africa Publish in high-impact journals Contribute to data visualization platforms Required Qualifications Ph.D. in Atmospheric
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identifying, analyzing, interpreting, and visualizing trends and patterns in complex data sets. Gaining knowledge of state-of-the-art statistical, analytical, and visualization methods and techniques through
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metabolic pathways and targets. Data analysis and integration using R and/or Python, including statistical analysis, visualization, and multi-omics data handling in collaboration with the team. Collaborating