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; Geology; Health and Medicine; Mathematics/Statistics; Materials Science and Physics; Psychology and Psychiatry; Technology, Data, and Computer Science; and Zoology.
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, and related health outcomes Conduct and oversee statistical analyses using large datasets and ongoing lab studies Develop and contribute to conceptual and theory-driven papers addressing addiction
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on manuscripts examining ultra-processed foods, addictive processes, eating behavior, and related health outcomes Conduct and oversee statistical analyses using large datasets and ongoing lab studies Develop and
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, including panel regression, analysis of large administrative data, survey data, and statistical programming in Stata/R/etc; excellent oral and written communication skills in English; a commitment to academic
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Machine Learning Seminar Group Advanced Tutorial Lecture Series on Machine Learning Non-Parametric Bayes Tutorial Course (October 9, 16 and 28, 2008) Bayesian statistics in other labs Machine Learning and
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-resolution MS and quantitative LC-MS/MS. Experience in targeted and untargeted metabolomics workflows, advanced data analysis (including multivariate statistics), and multidisciplinary collaboration is
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. The project will require an interdisciplinary effort, combining epidemiology, statistical modelling, and software development. In this role, you’ll lead the design and implementation of simulation studies
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statistical methods including multilevel modelling, psychometric scale validation (EFA/CFA), structural equation modelling and causal inference approaches appropriate for complex education datasets. Advise
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. Computer Science, Statistics, Data Science, Health Informatics, or related field) Proficiency in relational database design, construction and querying (SQL) Proficiency in Python and/or R for data
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professional development modules/workshops (e.g., responsible conduct of research, statistics, grant writing, application preparation, CV/ personal statement workshops, interview skills). Maintain accurate