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. Electrophysiology and MRI Data Analysis of Patients with Lennox-Gastaut Syndrome About Us: Stanford Pediatric Epilepsy Research is at the forefront of research in neuroscience, focusing on understanding complex
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environment provides many professional growth opportunities in academia, entrepreneurship, and public service. Responsibilities include: Investigate cutting-edge techniques in system modeling, analysis, and
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personalized learning experiences that are both effective and engaging. The first component of this work is to develop AI-augmented tools that enable elementary school-aged children to rapidly create
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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
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. Required Qualifications: A doctoral degree (PhD, MD, or equivalent) conferred by the start date. Proficiency in R/Python Experience with scRNAseq, and/or spatial proteomic/transcriptomic data analysis Growth
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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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. Applicants should be independent thinkers and willing learners, ambitious and team players, with a strong research publication record and a high-level understanding of programming and biostatistical analysis
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longevity and health span and, through those prediction, inform a variety of individual-level and community-level policy making efforts. The results of the analysis and investigations will inform design and
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research design and/or data analysis exercise as part of the interview process. Does this position pay above the required minimum?: Yes. The expected base pay range for this position is listed in Pay Range
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transmission modeling, statistical modeling, spatial data analysis, and cost-effectiveness analysis. In parallel, we conduct research on vaccine-preventable infections, developing and evaluating predictive