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; a global network of campuses and partners for students and faculty to leverage for learning and research; a deep investment in lifelong and experiential learning; a premium placed on pedagogical
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. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during
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; a global network of campuses and partners for students and faculty to leverage for learning and research; a deep investment in lifelong and experiential learning; a premium placed on pedagogical
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designs such as observational study, randomized clinical trial, adaptive randomizations, Bayesian analysis of randomized trials, conventional meta-analysis, meta-regression, and network meta-analysis Work
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randomizations, Bayesian analysis of randomized trials, conventional meta-analysis, meta-regression, and network meta-analysis. · Develop as an educator by taking an active teaching role in POCUS and EBM
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; maintain version control and prepares data for submission to public repositories and collaborative networks. Conduct statistical and spatial analyses of ecological and climate datasets. o Implement
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high-dimensional neural data. Approaches used include neural network-based approaches, Bayesian inference, and more Assisting with the oversight of day-to-day functions of the lab and shared lab spaces
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, China [map ] Subject Areas: Network/Dynamical Systems and Statistics Appl Deadline: 2025/12/31 11:59PM (posted 2025/01/01, updated 2025/01/20) Position Description: Apply Today is the last day you can