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given to candidates studying early China using analytical methods such as zooarchaeology, paleobotany, ceramic analysis, and lithic analysis. The successful candidate will be expected to: Teach one course
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for Biomedical Informatics Research at Stanford University. This position emphasizes conducting real-world evidence studies using various causal inference methods (e.g., target trial emulation) to examine
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systems. Includes establishing medical reasoning benchmarks and automated / scalable evaluation methods. Developing recommender algorithms to predict specialty care with large-language model based user
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(community interventions, community-based participatory research, meta-analysis and bias in research, RCT methods, causal interference, mathematical modeling, and econometrics) Policy research related
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theoretical modeling, remote imaging, and direct observation. Our research has both fundamental and applied elements. The successful candidate will demonstrate exceptional academic achievement and promise, and
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factor. However, non-U.S. scholars must be eligible for a J-1 visa, (with sponsorship from Stanford). Exceptions must be discussed with program administration. Email energy_postdoctoral_fellowship
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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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and make sue of some of the new methods we have developed, with a particular focus on human immunology and diseases. Required Qualifications: Ph.D in some area of immunology Enjoy collaborative work and
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. Requirements are a Ph.D. in immunology, publications and a willingness to learn and make use of some of the new methods we have developed, with a particular focus on human immunology and diseases. Required
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of the adaptive immune response to blood coagulation factor proteins deficient in individuals with the inherited bleeding disorder hemophilia, namely factor VIII and factor IX. The goal of the laboratory’s work is