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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 13 days ago
machine learning-related discipline. Strong publication track record in top ML, computational chemistry, or computational biology conferences and journals. Proficiency in Python, demonstrated through
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basic scripting in Image J, Matlab and Python - Excellent attention to detail and record keeping - Excellent time and project management skills Before applying, please note that to work at McGill
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engineering, electrical engineering, data science, or a related field. Skills in embedded systems development, electronics, or IoT (C/C++, Python, Arduino/ESP32, etc.) OR in machine learning and sensor data
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analysis and multivariate statistics (preferably using Python), to enhance building energy performance (and/or reduce building greenhouse gas) Experience in the full spectrum of research activities including
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modelling workflows using Python, Julia and/or R. Education/Experience: PhD in related field with 5 years experience following PhD (PhD received in 2020 or earlier). Strong computational and environmental
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skills, including experience with large datasets, statistical modeling, and computational tools (e.g., Python, MATLAB, R). Excellent communication and collaboration abilities with the ability to present
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completion to deadlines. Develop scripts and data processing pipelines using R or Python, leveraging advanced expertise for data processing, model development, and data visualization. Work with senior staff
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variety of data analysis tools and software. For example, MS Excel, R, Python, SPSS, Tableau, etc. Strong skills in data visualization and communication through charts, graphs, and other formats
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the purchasing of equipment and materials. Qualifications: Attention to detail. Proficiency with Python and other programming languages. Available on weekends Education/Experience: Experience working with animals
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. Strong coding skills in Python or a comparable programming language are expected, with the ability to develop analysis pipelines and tools that meet project deadlines and are suitable for publication