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Undergraduate degree in Applied Science, Engineering, or a related discipline. Minimum of three years of related experience, or the equivalent combination of education or experience. Proficiency in Python, with
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, Genetics, Cell Biology, Biophysics or a related field - Competency in computational (R or Python) and statistical analysis - Competency in experimental design and standard molecular biology, imaging
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statistics, data management). Comfort handling large and diverse datasets. Strong coding skills (R and/or Python), with experience using a high-performance computing platform (e.g., Digital Research Alliance
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taxonomy in AI-assisted workflows Prototype and test automated classification scripts (Python/R) Document data pipelines and QA/QC procedures Supervision & Training Mentor PhD-level and undergraduate RAs
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systems (RTOS) such as FreeRTOS or Zephyr. Experience with cloud-based data ingestion and analytics tools. Proficiency in programming languages including Python, C++, and/or Java. Familiarity with IoT
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provision of other research support and assistance. It is required to have some familiarity with Métis and/or Indigenous research, protocols and communities. Experience and knowledge of GIS mapping systems is
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and scalable pipelines (e.g., using Snakemake, Nextflow, or custom scripts). Automate common data processing workflows in bash, R, or Python. Maintain version control using GitHub and contribute
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, spatial modeling, and/or remote sensing is desirable. Proficiency in GIS, R, and/or Python for data analysis, modeling, and spatial analysis is also desirable Excellent written and verbal communication
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). Advanced Statistics: Preferably graduate students in Statistics. Data Science in Python/R: Preferably those with project experience in each language. AI/Society: Preferably those with programming experience
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) Qualifications Knowledge of python or matlab Basic statistical knowledge, e.g., linear regression, Fourier analysis, statistical significance, etc. Before applying, please note that to work at McGill University