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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 1 month ago
posted in accordance with the CUPE 3902 Unit 3 Collective Agreement Course: GGR322H5F: GIS and Population Health (Sci) Description: The purpose of this course will be to develop an appreciation
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University of Toronto Faculty of Information Sessional Lecturer Winter Term 2026 (January - April) INF2179H – Machine Learning with Applications in Python Course Description: Machine learning has
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University of Toronto Faculty of Information Sessional Lecturer Fall Term 2025 (September - December) INF2102H – Geographic Information Systems (GIS) in Libraries Course Description: This course
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 2 days ago
, the successful candidate will have the following duties: Modelling analysis including the use of statistical packages by R and Python programming Environmental modelling analysis and data visualization on a map
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 2 days ago
undergraduate teaching labs. Note: As part of your application, you must submit links to 1-3 pieces of code you have written in C++ or Python. This can be github accounts, course assignments or personal projects
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. Strong coding skills in Python or a comparable programming language are expected, with the ability to develop analysis pipelines and tools that meet project deadlines and are suitable for publication
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, AWS Glue, Talend, etc.). Proficiency in SQL, Python, and/or other programming languages commonly used in data engineering as well as data transformation tools (e.g. DBT). Solid understanding of database
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, learning, and research requirements. They are subject matter experts; they are skilled in research data management, collections, statistics, GIS, metadata, digital preservation, scholarly communications
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selection-mass spectrometry or a similar technique, mass spectrometry for characterizing chemical mixtures or proteomic samples, and programming in Python or C. The ideal candidate should have experiences
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using Python. Python and IBM Watson Analytics are modeling and visualization software used in this course. Practical aspects of computational models and case studies in Interactive Python are emphasized