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BIDS Data Science Fellowship

Application Deadline: 
Saturday, Apr 1st 2017

We are excited to invite applications for our next cohort in the BIDS Data Science Fellow Program. 

Successful applicants will join our current cohort of fellows in helping advance data analysis in the research sciences. BIDS data science fellows are postdoctoral scholars, graduate student researchers, or staff with excellent credentials in their fields as well as strong interests in advancing data-intensive approaches with a community of like-minded individuals from across campus. 

Each data science fellow will become part of and contribute to a growing ecosystem that brings together faculty, postdoctoral researchers, students, staff, and alumni to form a strong network that assists researchers in advancing data-analysis methods and inquiry, expanding and building new software and analytics tools, sharing best practices, and more. Information on our current working groups and projects can be found here.

Your data does not have to be “big data” to become a fellow. If you find your data-related problems to be at all unique and challenging, we welcome you to work with us. In particular, we are interested in applications from individuals exploring topics that may broaden the research diversity of our community and from those who are interested in working to help others elevate their approach to research.

This year, for the first time, in addition to our open call for Moore/Sloan Data Science Environment fellows, we are introducing several opportunities where fellows can be additionally engaged in collaborations with our partner institutions, including the UCSF Institute for Computational Health Sciences; Lawrence Livermore National Lab; Center for Law, Energy, & the Environment; Biomedical Big Data Training Program; Clean Energy Research Center for Water-Energy Technologies; and Data Science Education Program.


How to Apply: 

To learn more about our call for applicants, please visit our application page.

Letter of intent due April 1, 2017