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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 2 months ago
Methods in Linguistics - Fall 2026 Course description: An introduction to experimental design and statistical analysis for linguists. Topics include both univariate and multivariate approaches to data
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for faculty to teach courses in Biostatistics, Categorical Data, Computationally Intensive Methodology, Econometrics, High-Dimensional Statistics, Multivariate Statistics, Statistical Machine Learning
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at the crossing of statistics and machine learning. Modern vessels produce vast amounts of multivariate data streams. The project addresses the development of trustworthy statistical and machine learning methods
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for subglacial bedforms across sectors of the Laurentide Ice Sheet; (v) carrying out spatial and multivariate analyses for palaeoglaciological interpretation. Assigned activities and expected results
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environment team they will join, as well as those working on the ANR TASAB project. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7330-NOEGAR-074/Default.aspx Requirements Research
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statistical analysis including multivariate methods, data reduction techniques, structural equation modeling, survival analysis and Bayesian hierarchical imaging models, graph neural networks. The specialist
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and metagenomic data. compile, manage, and analyze datasets with appropriate statistical methods including univariate and multivariate methods. lead preparation and publication of peer-reviewed
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Demonstrable ability in the use of multivariate statistics and state-of-the-art emulation (including physics-informed machine learning and neural operators) C2 Practical skills in computational inference
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of Lecturer. Salary commensurate with experience. The successful candidate will have a 2-2 teaching load, focused on introductory courses through multivariable calculus. They will join a team of lecturers
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interventions. Excellent command of advanced statistical methods, including longitudinal data analysis and complex multivariate analyses (e.g., structural equation modelling, SEM). Experience working