319 machine-learning-"https:"-"https:"-"https:" positions at McGill University in canada
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convection. The objective is to develop reduced but realistic models of cumulus life cycles that may be applied toward cumulus parameterization and/or machine-learning algorithms for predicting short-term
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, topographic data, land-cover data, and other environmental predictors. Designs and evaluates statistical and machine-learning approaches for modelling plant species distributions and assessing environmental
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devices. Develop, design and build electronic and electrical circuitry for installation. Modify and install various machines or circuits in support of experiments and for new laboratory set-ups. Draw plans
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for more advanced data analysis, statistical modeling, and machine learning applications. Creative, well organized and self-motivated, with strong analytical, planning and problem solving skills
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, quantum information theory, quantum programming languages, quantum compilation, and classical-quantum computer architectures. Position Description: The School of Computer Science at McGill University
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: The TA is expected to have strong Python skills and familiarity with data analytics and machine learning. Prior experience with text analytics, NLP, language models, or related methods is particularly
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conferences). Knowledge of existing AI ethics frameworks, fairness toolkits, and fundamental concepts behind value-sensitive design. Capable of assessing submitted machine learning models and code in Python
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of Computer Science Course Title: Machine Learning in Genomics and Healthcare Course Code: COMP 565 Estimated Number of Positions: 3 Total Hours of Work per Term: 90 Hiring unit: School of
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Undergraduate Student Advising (SOUSA). Together, we provide guidance and support to over 6000 undergraduate students; assisting them in making informed academic choices in light of their learning, career and
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competitive labor market. Primary Responsibilities: Deliver one-on-one coaching to students preparing for technical interviews. Conduct mock technical interviews covering coding, analytics, machine learning