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. Familiarity with omics approaches, including genomic, transcriptomic, and metabolomic analyses. Experience with developing and applying machine learning algorithms to analyze biological data. Application
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will also have the opportunity to contribute to algorithm development, software architecture design, and software implementation. The ideal applicant for this position will have several characteristics
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; or the training of a machine learning algorithm to read a digitized document written in an under-resourced language. Position description: The University of Toronto Libraries seeks a highly organized, flexible, and
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software and languages, such as SAS/R/Stata, to explore data validity, develop research variables/algorithms/flags, create analytic cohorts for each study, create sub-cohorts for trainee-led analyses, and
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, and explainability; developing unbiased algorithms and responsible data use; addressing the social impacts of AI and IT-induced biases; equitable compensation policies; combating labour discrimination
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to present complex data in an accessible and actionable manner. Develop and apply machine learning algorithms to analyze data and extract meaningful insights. Implement real time monitoring and processing
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, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging
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candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks include
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characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and