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organ-on-a-chip (OOC) models, colony picking and bioprinting). The ideal candidate should have strong expertise performing machine learning (ML), computational biology with the capability and/or
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title: CSC2515HS - Introduction to Machine Learning Please note, this position is a 0.5 FCE appointment. Course description: Machine learning (ML) is a set of techniques that allow computers to learn
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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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Sessional Lecturer, INF2205H - Designing Sustainable & Resilient Machine Learning Systems with MLOps
University of Toronto Faculty of Information Sessional Lecturer Winter Term 2026 (January - April) INF2205H – Designing Sustainable and Resilient Machine Learning Systems with MLOps Course
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Learning Course Description: Machine Learning applications are increasingly utilized to make crucial decisions in many sectors of our economy and society. These include, but are not limited to, healthcare
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analysis of experimental data with additional insights into data mining and evaluation of machine learning. The course will use the R statistical package. However, the main principles of data analysis
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industry/upskilling educational programs, course designs, and developing workshops for STEM subjects, including but not limited to machine learning, robotics, laboratory automation, and materials discovery
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 5 hours ago
skills. Excellent analytical and problem-solving skills. Familiarity with technology and emerging trends in machine learning and artificial intelligence applications within academic libraries. Active
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. The incumbent demonstrates and practices instructional leadership in the use of tools, machines and material selection along with assembly techniques, practical demonstrations, and safety. This position requires
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us: Student Life connects life to learning. We believe every student should have the opportunity to participate in university life actively and find connection and community while discovering new ways