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that gathers actionable data to advance science and inform data-driven, evidence-based early childhood policy, practice, and systems. To date, we have heard from more than 22,000 parents of young
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. This position will be located in the Center's Cancer Cell Therapy Data Hub, which is led by Dr. Zinaida Good and provides a collaborative environment that pushes the cutting edge of technology to learn from
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of the post-doc is to study how innovations in AI, especially adaptation of Large Language Models (LLMs) architectures for time-series data, can be used in study of aging, health span, and longevity
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of infectious diseases research and provides a strong community of scientific colleagues and students. Required Qualifications: The ideal candidate will have a PhD in Epidemiology, Engineering, Data Science
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applying data science principles and techniques to biomedical datasets. Applicants should be comfortable using coding skills such as SQL, R, and Python to extract data from databases, clean it, and analyze
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merits have been published in the premier science and technical journals. The group is well funded by NIH and industry partners. For more information, please visit http://med.stanford.edu/Gulab (link is
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-energy-food policies. We are looking for new team members who enjoy team-science and engineering and would thrive in a dynamic, curious, team-oriented, and industrially connected environment. Our projects
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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. Does
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population health research, including but not limited to Epidemiology, Urology, Public Health and Policy, Biostatistics, Computational and Data Sciences, Nursing, Psychology, and Sociology. An interest in
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assessments, direct new research priorities (both technical and applied), and to oversee the implementation of rigorous measurement methodologies at scale. More information about ROAR can be found at: https