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of an undergraduate degree in a related field. Training in causal inference and/or machine learning methods Effective oral and written communication skills Outstanding academic credentials and intellectual creativity
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research experience. Research track record should be demonstrated via prior publications in relevant venues in psychology, cognitive science, education, or human-computer interaction. Knowledge and expertise
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strong, demonstrated interest to conduct academic research in a relevant field Interest in legal research Interest in causal inference and social science Experience with machine learning / deep learning
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Epidemiology, Causal Inference, and EHR Data Integration Applications are invited for a postdoctoral fellow position in cancer epidemiology to join Dr. Summer Han’s research group in the Stanford Center
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Stanford University, Department of Statistics Position ID: Stanford -Statistics -ASSTPROF2526 [#30392] Position Title: Position Type: Tenured/Tenure-track faculty Position Location: Stanford
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(link is external) ); Monocle 2 and 3 for unsupervised pseudotemporal trajectories inference: Qiu et al., Nature Methods, 2017a/b (https://doi.org/10.1038/nmeth.4150 (link is external) , https://doi.org
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-scale, federated data analysis and integration. Scientific Visualization Workflows: Develop and automate workflows to generate scientific visualizations (e.g., ATAC-seq tracks for IGV) that compare
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Stanford University, Statistics Position ID: StanfordStatistics -AP202526 [#26866] Position Title: Position Type: Tenured/Tenure-track faculty Position Location: Stanford, California 94305
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experience in developing models to analyze temporal data. Prior experience in utilizing Bayesian modeling in related applications. Required Application Materials: CV Contact information for reference letters
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tracking, and refurbishing activities related to the physical environment and building systems. This is an individual contributor role. In this role, you will: Oversee, coordinate and manage the day-to-day