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The Shanahan Foundation Fellowship at the Interface of Data and Neuroscience
Neuroscience has a treasure trove of data waiting to be explored.
The Allen Institute is a leader in collecting large-scale, standardized datasets on the brain, working since 2003 to refine the data collection techniques needed to understand biology’s most complex system. Our data banks are ready and waiting. The next stage of discovery depends on experts from diverse technical backgrounds coming together to uncover new insights.
The Shanahan Foundation Fellowship at the Interface of Data and Neuroscience was created to provide freedom and flexibility to promising young scientists from diverse fields, as they work alongside neuroscientists at the Allen Institute and University of Washington. The three-year fellowship provides Ph.D.s from data science, computer science, physics, mathematics, and many other fields the mentorship and support to pursue their own research interests with our data.
Applications for the Fall 2024 cohort are due on February 1st, 2024.
"An exciting opportunity to make fundamental discoveries."
The Shanahan Foundation Fellowship at the Interface of Data and Neuroscience, funded, in part, by the Shanahan Family Foundation, was created to bring diverse, non-neuroscience perspectives to the neuroscience field. This is a collaborative program between the Allen Institute and the University of Washington. Fellows will work with mentors to develop novel research programs using the Allen Institute’s large data banks to push the boundaries of both data and neuroscience.
“We wanted to create the opportunity for fresh perspectives to join neuroscience. This fellowship is intended to give upcoming leaders in quantitative fields the opportunity to uncover new insights in the massive neuroscience datasets produced by the Allen Institute.”
— The Shanahan Family
Eligibility and application materials
You do not need experience in neuroscience to apply. Applicants must be scientists with a Ph.D. (or equivalent) or who will have completed their Ph.D. by the start of the fellowship. The Ph.D. should have been awarded in the last 3 years. The fellowship is appropriate for Ph.D.s in a quantitative field such as computer science, electrical engineering, physics, mathematics, or biology. They should have a strong background in statistical, computational, machine learning, or other data science methods. Up to three fellows will be selected each year. International applicants are eligible to apply and we provide immigration support.
Applications must include:
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