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involves reviewing onboarding and mentorship models from other institutions, identifying promising practices, and helping to design a phased onboarding plan tailored to the College. The RA will assist with
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to develop data-driven, space-time explicit precision agronomic solutions Utilizing high-performance computing (HPC) systems for large-scale geospatial data processing, model training, and validation Designing
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via GitHub repository) in statistical analysis and modelling using R or Python with open source code Experience with high performance computing environments, particularly Digital Alliance Canada
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