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analyses of these data for research, quality improvement and surveillance purposes. The incumbent will apply appropriate methods to aid in the creation of a learning health system around opioid-related
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analyses of these data for research, quality improvement and surveillance purposes. The incumbent will apply appropriate methods to aid in the creation of a learning health system around opioid-related
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Course description: A half-year capstone design course in which students work in small teams to apply the engineering design, technical, and communication skills learned previously, while refining
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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Science, or a related field. Strong programming skills in Python, R, or related languages for data analysis and machine learning. Experience with genomics data analysis, health informatics, or computational
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procedures (e.g., multilevel modeling, longitudinal data analysis, machine learning algorithms), cleaning and structuring large datasets, validating model assumptions, and ensuring reproducibility. Synthesizes
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development and target discovery challenges. Qualifications: PhD in bioengineering, computational biology, machine learning, systems immunology, or related discipline, obtained within the last 5 years, by
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discovery challenges. Qualifications: PhD in bioengineering, computational biology, machine learning, systems immunology, or related discipline, obtained within the last 5 years, by the time of
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environment. Proficiency in learning management systems and other computer applications as required.
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at McGill University), do not apply through this Career Site. Login to your McGill Workday account and apply to this posting using the Find Jobs report (type Find Jobs in the search bar). To teach visual