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, scalability and Amdahl's law, Flynn taxonomy, vector processing and parallel computing architectures. Reference: https://artsci.calendar.utoronto.ca/course/csc367h1 Estimated course enrolment: 125 students per
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 11 hours ago
Description: Course number and title:CHMB62H3: Introduction to Biochemistry Course description: This course is designed as an introduction to the molecular structure of living systems. Topics will include
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, and their lived experience shall be taken into consideration as applicable to the position. The University of Toronto invites all qualified applicants to make application. The University strives to be
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 10 hours ago
hours, emails, etc.; invigilating the final exam; managing the grades and submitting the final course grades; dealing with student petitions, setting and grading a make-up exam if required. How to apply
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- $65,000/annually. University of British Columbia, Perrin Laboratory (https://perrin.chem.ubc.ca/) We are seeking a highly motivated DNA/Aptamer Chemist to join a multidisciplinary research team developing
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 10 hours ago
a diverse and inclusive team of public safety professionals that collaborates with students, staff, and faculty to build a safer and more connected campus experience. Security Services believes
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should submit an application form (available here: https://hrandequity.utoronto.ca/wp-content/uploads/sites/26/2016/04/Employment-CUPE-3902-Unit-3-Application-Form-June-2012b.pdf ), a letter of interest
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 11 hours ago
: [[positionNumber]] Existing Vacancy: Yes Description: Course number and title: EESA06H3 - Introduction to Planet Earth Course description: This general interest course explores the composition, structure and origin
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uncertainty and learning from new data. The course introduces the basics of Bayesian inference and Markov chain Monte Carlo methods, then shows students how to compute and make inferences for complex data
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pipeline. Research programs may leverage structure-based models, protein language models, generative AI, or novel hybrid approaches. Areas of interest include, but are not limited to, developing predictive