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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 2 months ago
MMI1020H Big Data Analysis This course introduces students to the art and science of data analysis and provides a set of statistical and econometric tools that are useful in managerial decision
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: Introduction to the Big Data Era & Opportunities for Better Health Care Department Research and Experimental Medicine Support | Department of Medicine | Faculty of Medicine Compensation Range $38.65 - $38.65 CAD
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environmental, climatic, geographic, and biodiversity datasets. Compiles, cleans, and integrates large ecological datasets, including plant occurrence records, climate variables, remote-sensing products
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Primary Purpose: To contribute to the efficient operation of the Large Animal Hospital by providing technical assistance to clinicians and undergraduate students. Nature of Work: Reporting to
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Applications are invited from qualified individuals for a full-time tenure-track faculty position in Beef Cattle Research and Extension in the Department of Large Animal Clinical Sciences (https
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+ years of progressive experience in data governance, data analysis, data management, data quality, or related roles within large, complex organizations, preferably in Higher Education. DAMA Certified: Data
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. Demonstrates a commitment to enhancing one’s own awareness, knowledge, and skills related to equity, diversity, and inclusion. Preferred Qualifications Extensive experience with data analysis in large ERP
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the laboratory of Professor Adil Harroud, the Research Associate will lead the statistical genetics and bioinformatics analyses of large-scale genetic, proteomic and clinical datasets in multiple sclerosis and
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, guiding and managing a large, diverse, and complex facilities operation; organizing and reorganizing work of teams and service providers as needed to meet service and financial needs, and ensuring
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databases, specifically in fisheries. Proficient in Python, R, SQL, and MS Excel to work with large datasets (over 1 billion rows). Familiar with packages such as Pandas, scikit-learn, and PyTorch for data