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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 1 day ago
implementation science, health services research, survey research, epidemiologic methods, or measurement development. Experience with REDCap, NVivo, and/or quantitative or statistical analysis software. Experience
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health data statistical analysis, physiological experimental data processing, and psychological health empirical research methods. Familiar with academic paper writing and international biomedical research
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to identify molecular processes associated with variation in brain morphology, connectivity and function. The fellow will work at the interface of neuroscience, statistical genomics and computational analysis
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Analysi s Experience analysing high-dimensional biological datasets. Proficiency in R for statistical analysis, visualization, and reproducible data analysis. Experience with packages such as Seurat
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approaches (e.g., using R, NetLogo, or similar) Working knowledge of ecological (especially landscape ecology) research methodology and biostatistics Computer proficiency, including use of statistical software
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advanced biostatistics Computer proficiency, including use of statistical software for spatial analyses, such as ArcGIS, QGIS, R, Google Earth Engine Experience assembling, organizing, and analysing large
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systems Working knowledge of ecological (especially landscape ecology) research methodology and advanced biostatistics Computer proficiency, including use of statistical software for spatial analyses
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Qualifications PhD in computer science, clinical informatics, statistics, or a closely related field, conferred within the past five years. Demonstrated experience in health data visualization, interactive
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through the development of more effective diagnostic and therapeutic approaches. Qualifications and Experience · PhD in Bioinformatics, Computational Biology, Statistics, Genetics, Genomics, or a
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research funding; and · Collaborating with other research teams. Qualifications: The qualified candidate will have a doctorate degree in a relevant discipline (i.e., Epidemiology, Statistics