Sort by
Refine Your Search
-
meet tight deadlines and focus on attention to detail Demonstrated high level of customer service skills Demonstrated ability to speak in large group settings Highly developed oral and written
-
on promoting advances in person-centered care. The successful candidate will be part of a large, academically successful rheumatology unit with a clinical role aligned with divisional and departmental priorities
-
data modelling and query performance tuning on SQL Server, MySQL, and Azure platforms. Experience working with large and complex data sets, as well as, experiencing analyzing volumes of data. Experience
-
large prize postdoctoral program (the Dunlap Fellowships ) and has substantive programs in professional training, such as the yearly Dunlap Instrumentation Summer School, education (Discover the Universe
-
leading researchers in various fields, and are actively engaged in outreach programmes. The Dunlap Institute has a strong focus on developing innovative astronomical technologies, has a large prize
-
experience to apply those skills toward imaging data (e.g., live cell microscopy). The successful candidate will contribute to advancing machine learning-driven analysis of high-content imaging data to achieve
-
economic hub of Canada, and the city is renowned for its cosmopolitanism and multiculturalism. As a large department working in a wide range of subfields, the Department of Sociology is very highly ranked
-
University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 2 hours ago
assignments. The major project for the course will involve a large health data set that teams will compete to analyse. . Estimated course enrolment: 19 Estimated TA support: 40-50 Class Schedule: Specific
-
the research objectives of AC faculty and industry partners. Using SDLs to synthesize and characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting
-
characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and