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, MacOS, and Windows. The ability to write and document programs in a number of high-level languages such as R, Python, and UNIX shell is required. Effective verbal and written communication with staff and
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career-driven, experienced in project management and engagement, possessing strong communication skills, and with aspirations to expand their skills and move into a Research & Development (R&D) leadership
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- Proficiency in R and/or Python programming - An interest in interdisciplinary research spanning ecology, remote sensing, spatial analysis and mathematical ecology - Experience in writing and publishing peer
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such as R or Python. The ideal candidate will be comfortable working with large geospatial datasets and interested in collaborating as part of a team on various CanN2ONet modelling initiatives. Experience
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/Abilities: Demonstrated coding ability with Perl, Python, R, bash or SQL in a Linux environment Practical experience of networking and administration of Linux servers Understanding of common IT/Networking
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types, basic concepts of regression) • Familiarity with spatial analysis/GIS concepts • Experience with R for statistical analysis GEOG 203 Environmental Systems Key Responsibilities For hydrology, soils
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Windows and Linux environments, and using the following software: MSOffice, SPSS or R, and Matlab. Experience using SPM, FSL, ANTs, PLS and/or AFNI or similar image analysis software is required. Excellent
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planning. Coursework or research experience in road safety, traffic modelling, or transportation planning. Proficiency in working with open data sources for traffic and transit operations using R, Python
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., instrumental variables, propensity score matching, and treatment effects). Familiarity with one or more statistical software packages (e.g., R, Stata, Python) for data analysis. Research Aptitude: Demonstrated
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. Proficiency with programming languages such as Python, R, MATLAB, or similar. Hands-on experience with machine learning frameworks and tools. Experience with real-time data processing and stream processing