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: This project, situated at McGill University's Peter Guo-hua Fu School of Architecture, explores the dynamic interplay between contemporary art and architectural exhibitionary spaces. By focusing on how
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of intrauterine devices vs. oral contraceptives in relation to ovarian cancer incidence. The postdoc will join a team of McGill University professors and researchers at St. Mary’s Research Centre and the Lady Davis
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appropriate to assigned tasks, • Assist with preparation of reports and manuscripts, • Collect and analyze qualitative and quantitative data, • Review and become familiar with relevant literature, • Assist with
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appropriate to assigned tasks, • Assist with preparation of reports and manuscripts, • Collect and analyze qualitative and quantitative data, • Review and become familiar with relevant literature, • Assist with
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for publication in peer-reviewed journals. Job Responsibilities: Conduct literature reviews and contribute to academic publications resulting from the project. Establish pipelines for generating synthetic
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observation and experimental systems). Project personnel will use state of the art data science and statistical approaches in the context of emerging frameworks for detecting and attributing biodiversity change
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personnel will use state of the art data science and statistical approaches in the context of emerging frameworks for detecting and attributing biodiversity change. Sentinel Postdoctoral researchers will be
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-generation disease models, making MouseTRAP a state-of-the-art platform for assessment of robust, reproducible and human-relevant cognitive outcomes in mouse models, for either fundamental discovery research
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custom-designed state-of-the-art imaging software, lighting, display capabilities, and a sample presenter. To assess unique attributes associated with individual kernels during distinct sprouting phases in
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. • Advanced skills in statistical programming and modeling. • Advanced skills in geospatial data analysis. • Familiarity with state-of-the-art biodiversity and ecosystem models. • Knowledge of integrated