Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred
-
University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 21 days ago
- Population Genetics Course Description: This course introduces students to the genetic variation between and within populations. The topics include evolutionary forces, quantitative genetics, and Bayesian
-
Studies Course description: The use of proxy data (terrestrial and aquatic microfossils) to infer past environmental conditions. The nature and extent of Quaternary environmental change is considered in
-
Sessional Lecturer, INF2205H - Designing Sustainable & Resilient Machine Learning Systems with MLOps
Description: Decision-makers in modern organizations rely on machine learning systems to infer insights from information by analyzing meaningful patterns in the connections and associations within data. Leaders
-
experience Minimum five (5) years recent and related experience Experience in applied statistics (multivariate models and distributions, jump processes, inference), e.g. simulation tools such as Monte Carlo
-
seminars, coordinating event and travel logistics, maintaining project timelines, creating and updating filing and internal documentation systems, and tracking deliverables. Experience overseeing and
-
a university environment. Experience with record keeping, tracking and maintaining spreadsheets and databases. Experience providing routine answers to a wide variety of stakeholders. Demonstrated
-
University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 days ago
) Qualifications: CPA (qualified) with significant professional marking experience Description of duties: Creating and marking assignments Individual debrief with students Maintain and track grades Invigilating
-
weekly lectures (in-person); grading student work; tabulating and tracking grades; invigilating tests and exams; holding office hours for regular meetings with students. Application Procedure:All
-
asynchronous); leading one or more tutorial sections (in-person, times TBD); grading, tabulating and tracking grades; invigilating tests and exams; holding office hours for regular meetings with students