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and collaboration in low-and-middle-income countries and good knowledge of R or other software for data management, analysis and visualization. The position does not require teaching, but it may be
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a postdoctoral fellow at the University. The individual cannot have held previous positions in the professional ranks. Preferred Qualifications Experience with NGS data analysis and Linux based HPC
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analytical and modeling skills, including data science, database management, data visualization, etc. Strong publication record Experience working on subjects related to one or more of three main research
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The University of North Carolina at Greensboro | Greensboro, North Carolina | United States | 2 months ago
will perform grant-funded research projects, including experimental design, sample preparation, data acquisition, data analysis and interpretation, research presentation at national/international
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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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high-quality peer-reviewed research articles, present findings at scientific conferences and professional meetings, contribute to data visualization, figure preparation, and professional scientific
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livable cities. The ideal candidate would have strong experience in some of the following areas: quantitative and qualitative data collection and analysis, geospatial data analysis, urban design, data
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scientific publication and writing articles in international journals; 8) Experience in data visualization tools and advanced statistical analysis (e.g., pandas, scikit-learn, matplotlib, seaborn, SHAP
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combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. For more information about the total announced post-doctoral
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contributes to ARAC’s scientific portfolio through independent data analysis, development of computational workflows, integration of genomic and epidemiologic datasets, and coordination of research activities