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issues. Provides supervision and mentorship to trainees and staff. Teach trainees how to use basic Python and R coding to perform beginner – intermediate level analyses. Present research findings to others
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and conferences. Proven experience in design and implementation of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas
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desirable. Proficient in Python, R, and ML libraries such as PyTorch or TensorFlow. Strong communication and collaboration skills; ability to work independently and as part of a team. Willingness to respect
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 20 days ago
in Linux and Windows scripting including Python, BASH and Powershell Experience working with hypervisor infrastructure such as VMware in a production environment Extensive experience with Linux-Active
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candidate will have strong data analysis skills, attention to detail, and an ability to work independently. Qualifications: Experience with data collection and cleaning • Programming experience in Python
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. To perform this role, the incumbent will need to possess various technical skills, including proficiency in SQL, Python, R, or SAS, and have experience working with visualization technologies such as Tableau
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). Advanced Statistics: Preferably graduate students in Statistics. Data Science in Python/R: Preferably those with project experience in each language. AI/Society: Preferably those with programming experience
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, etc.). Experience using Python and/or R for data analysis and visualization, including for analyzing spatial data (e.g. using geopandas, pysal, etc.). Experience in front-end web development (HTML, CSS
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) Qualifications Knowledge of python or matlab Basic statistical knowledge, e.g., linear regression, Fourier analysis, statistical significance, etc. Before applying, please note that to work at McGill University
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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