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in the course. Must be familiar with programming in Python. Must be willing to interact with students in the lab. Must also have good command English language and must possess good communication skills
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systems and data acquisition using LabView and Python. Condition of employment Reliability Status For a Reliability Status, verification of background information over a period of 5 years is required
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scripts to process and analyze behavioural and neuroimaging data in languages such as Python, Matlab, or Bash and/or using standard neuroimaging analysis software; Conducts statistical analyses using tools
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 23 days ago
, including data manipulation, descriptive analytics, basic statistical analysis, and data visualization. Experience using common analytics tools and programming environments such as Python, R, Excel, SQL
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monitoring. Familiarity with computational image analysis, scripting (Python, MATLAB), or machine learning–based image workflows. Experience with method development, imaging assay optimization, or pipeline
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, Engineering, Health Informatics, Data Science, or a related discipline. Strong, demonstrated proficiency in Python for data engineering or software development applications. Demonstrated ability to act as a
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data analysis tools (e.g., R, Python), information management, and basic web or visual communication tools is an asset. Interest in sustainability, environmental research, and interdisciplinary
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Proficiency in Microsoft Office and experience with statistical software (R, STATA, SAS, or Python). Strong organizational, communication, and time management skills. Ability to work independently and
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Qualifications Experience with hyperspectral data acquisition and analysis, including Python-based workflows. Familiarity with machine learning, data integration, and advanced visualization tools for exploration
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cross encoder architectures and retrieval augmented generation. Strong programming skills in Python and deep learning frameworks, familiarity with MLOps practices, data governance for sensitive health