Data Science Postdoc Fellowships

The call for applications for 2024 is now open. Apply by December 22, 2023!

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Our mission: 
enable data-driven discovery at scale and expand data science education 
-across Stanford and beyond

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What's Happening

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Collaborative Efforts

Research

Stanford Data Science is a collaborative effort across many departments in all seven schools. We strive to unite existing data science research initiatives and create interdisciplinary collaborations, connecting the data science and related methodologists with disciplines that are being transformed by data science and computation.

Explore our research

Education

Stanford Data Science connects departments, schools, and programs from all areas of campus to provide diverse data science educational opportunities at the undergraduate, graduate, and professional levels.

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World map made with strings and the words above read: "Weaving data science into the fabric of the university"

Community

Stanford Data Science is helping to weave data science research into the fabric of the university and connect with our peer universities, not-for-profit organizations, and corporate partners.

Reach our community

Data Science for All

Weaving data science research and methods into the University's fabric, giving our faculty and students the tools, skills and understanding they need to do the cutting-edge research that will drive 21st-century scholarship and education.

Accelerate Research

Computing for Data Science

A seminar-style course jointly supported by the Statistics department and Stanford Data Science, and suitable for doctoral students engaged in either research on data science techniques (statistical or computational, for example) or research in scientific fields relying on advanced data science to achieve its goals.

Course Info

Women in Data Science

The Women in Data Science (WiDS) initiative aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. WiDS started as a one-day technical conference at Stanford in November 2015.

Women in Data Science