428 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" positions at McGill University
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. Learning outcomes: By the end of this course, the students will be able to: Describe the purpose of primary hardware and software components of computer networks. Explain the fundamental concepts of common
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through the McGill Learning Management System (currently myCourses). Administer all aspects of the logistics of written examinations. Act as chief invigilator. This includes training invigilators, assigning
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: Department of Electrical & Computer Engineering Term: Winter 2026 Course subject code: ECSE 536 Course Title: RF Microelectronics. Course Credits: 3 credits Location: SH680 1255 Schedule: Tuesdays & Thursdays
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course lecturer position to teach in Winter 2026. Please include your cover letter and Curriculum Vitae and if applicable a copy of your Study/Work Permit. A brief course outline is optional. MECH 289
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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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term before application, for training during class tutorials. Basic knowledge of metrology instruments, how to use and read caliper, what are coordinate measuring machines and measurement probes. Basic
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course lecturer position to teach in Winter 2026. Please include your cover letter and Curriculum Vitae and if applicable a copy of your Study/Work Permit. A brief course outline is optional. MECH 289
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client service for our executive participants. The virtual training programs are an important component of the MEI learning platform and contribute to the overall MEI revenue. We are looking to extend
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position is based in the Department of Electrical and Computer Engineering. Position Summary: Under the direction of the immediate supervisor, provides administrative support for academic student affairs
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field. Demonstrated experience with single-cell and/or spatial transcriptomic analysis (Scanpy, Seurat, Squidpy, etc.). Strong programming proficiency in Python and R; experience with machine-learning