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developing schedules, coordinating deliverables, and supporting implementations Experience designing and supporting scientific computing workflows using tools and technologies such as Python, R, MATLAB, Julia
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/geospatial analysis (e.g., Python, R, GIS) skills are considered an asset. Applicants are asked to submit one bookmarked pdf file: (1) curriculum vitae; (2) a maximum 1-page letter of interest describing your
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laboratories in the development, evaluation and characterization of engineered materials and/or hydrometallurgical processes. Recent experience in writing automated data analysis/data handling scripts in Python
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programming skills, with experience in R, Python or comparable scientific computing environments. · A record of rigorous research and peer-reviewed publication appropriate to career stage. · Ability to work
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Learning), COMP 345 (From Natural Language to Data Science), COMP 550 (Natural Language Processing). Advanced Statistics: Preferably graduate students in Statistics. Data Science in Python/R: Preferably
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combination of equivalent experience. Minimum five years. Demonstrated experience in infrastructure automation coding using scripting (Bash, Python, PowerShell or equivalent). Strong experience in maintaining
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or related industries with significant research and development. Experience with data pipeline tools and platforms (e.g., Apache Airflow, AWS Glue, Talend, etc.). Proficiency in SQL, Python, and/or other
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, Python, SQL and Markdown ● Proficiency in version control tool Git/Github ● Strong interests in human fMRI analysis ● Strong interpersonal, organizational, and verbal and written
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the organization. Knowledge in data extraction and manipulation Technical experience with analysis and visualization tools (e.g. Excel, Power BI, Tableau, R, …) Proven experience with the usage of Python, SQL or DAX
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, spreadsheets, data visualization, and statistical or qualitative-analysis software. Experience with R, SPSS, SAS, Python, NVivo, Power BI, or similar tools is an asset. Familiarity with privacy, confidentiality