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, and anti-racism, • Experience working with historically marginalised populations, • Prior experience in working with health administrative databases, causal inference methods, biostatistics
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the least squares linear regression model in depth and may introduce models for discrete dependent variables as well as the maximum-likelihood approach to statistical inference. Emphasis on the assumptions
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quantitative research, particularly methods for longitudinal analyses, causal inference, and natural experiments (e.g. difference in differences, interrupted time series) Demonstrated experience (as demonstrated
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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
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methods is an asset Knowledge of Bayesian statistics is an asset Excellent written and oral communication skills Strong analytical, problem-solving, and programming skills (in statistical software such as R
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of inference and reconstruction in archaeological interpretation. August 27 – December 3, 2025: Tuesday & Thursday (8:35 - 9:55 am) Leacock 617 Teaching Qualification Requirements: Education : MA required
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: - Collect quotes from the event - Compile and formulate a post event research report based on the outcome of the event - Collect and record key take aways from the event - Infer and analyze the implication
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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
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History EPSC 240 Geology In The Field EPSC 320 Elementary Earth Physics EPSC 340 Earth and Planetary Inference EPSC 423 Igneous Petrology EPSC 519 Isotopes in Earth and Environmental Science EPSC 530
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 months ago
(UTSC) invites applications for a full-time tenure stream position in the area of Statistical Sciences, with a focus on the theory of Bayesian statistics and uncertainty quantification. The appointment