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employ advanced analytical methods in large databases, which include claims data and electronic health record data in conventional structures and in common data models. Our research group prioritizes a
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paradigms in primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science
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Application Materials: Please send your application package as a zipped file to kseetah@stanford.edu (link sends e-mail) , with the subject line: Application for 'Integrating Natural and Cultural Data' postdoc
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expertise in large language models (LLMs) and electronic phenotyping to join our dynamic team focused on advancing cancer research through innovative data-driven approaches in the Cancer Data Science Core
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urgent questions of practical relevance and to design studies to test pragmatic solutions, analyze data, and disseminate findings and implications. The program will also provide fellows with training in
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for aging populations Why Join Our Fellowship? World-Class Mentorship: Receive primary mentoring from Dr. Periyakoil Access to a large network of research mentors across Stanford Medicine, School
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, and to utilize the unique data provided by tutoring to better understand teaching and learning. The postdoctoral fellow will contribute to this work by leading one or more of the following research
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. Data sources for our work in this area are large-scale electronic health record data, medical claims data, mortality registries, and epidemiological cohort studies. The researcher will be expected