2,550 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" positions in Canada
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diversity. We nurture a love of learning that will last a lifetime. We aim for academic growth in all subject areas. We prepare campers for leadership and service in society. We respond to challenges and use
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rapidly growing sectors. Join others in contributing to healthy, supportive communities and making a difference — A paat tsi kani takiiks (those that create sparks). To learn more about the Faculty
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skills Basic computer proficiency, including daily use of StarRez maintenance software 6-12 months of related work experience preferred Salary: $21.23 - $26.81 per hour Closing Date
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Teaching and Learning Compensation Range $30.96 - $35.51 CAD Hourly Posting End Date February 5, 2026 Note: Applications will be accepted until 11:59 PM on the Posting End Date. Job End Date June 30, 2026
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evening per week (from 5 to 7 pm or from 7 to 9 pm). The course lecturer will be required to develop conversation content for the assigned class fluency level(s) based on pre-defined workshop learning
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data visualization. The candidate should have experience with programming and data manipulation in Python. Experience programming and training convolutional neural networks for computer vision
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on their potential and demonstrated skills in teaching and research. The candidates should have a solid background or experience in multi-omics data analysis, including, for example, machine learning. Additionally
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using a virtual learning platform [e.g., Zoom, WebEx] and the McGill myCourses learning management system Before applying, please note that to work at McGill University, you must be both authorized
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combination of knowledge and experience. Experience working with Government computer-based programs such as ESP and MIDAS would be considered a definite asset. Applicants are asked to clearly describe in
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. Job End Date Ongoing At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and