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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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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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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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(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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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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microenvironment architecture that drives cancer progression and therapeutic resistance. The successful candidates will perform spatial omics profiling and analysis to infer biological and clinical insights and
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The Division of Gastroenterology and Hepatology has a long tradition of major contributions in basic research, a new commitment to clinical and outcomes research, a track record of training fellows for academic
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causal inference methods to examine efficient surveillance and treatment strategies using an integrated database of electronic health records from multiple healthcare systems. Applications are invited
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. Develop intuitive reports for molecular pipelines for tracking progress and quality metrics. Track reports for problems with pipeline analysis and underlying data. Extract relevant data from a variety of
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, emphasizing excellence in education, clinical practice, and research. The ideal candidate boasts a distinguished track record in scholarship, with a proven ability to secure funding and produce high-quality