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at the interface of data and neuroscience
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shanahan foundation fellowship

the shanahan foundation fellowship at the interface of data and neuroscience
apply here
explore stories
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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 mammalian brain, from the cellular to the whole-brain level, working since 2003 to refine the data collection techniques needed to understand biology’s most complex organ. 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 allied fields the guidance to pursue their own research interests with our data, with help from dedicated mentor .

Two professionals discuss data visualizations and charts displayed on a monitor during meeting.
Shanahan Fellow, Ryan Raut (right) shares neuroscience data insights with colleague, Liz Dueweke.
"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

shanahan fellowship applications

Applications for Fall 2026 will open September 15th and close December 1st, 2025.

Selected candidates will be invited to give virtual talks on February 2nd and 3rd, 2026. A subset of those candidates will then be invited for in-person interviews on March 2nd and 3rd.

Applications are now closed.

fellowship details

  • 3-year program for recent Ph.D.s to explore complex data in neuroscience at the Allen Institute and University of Washington
  • Neuroscience experience not needed—we’re seeking applicants with expertise in computer science, data science, engineering, mathematics, physics, and allied fields
  • Designed to provide freedom to explore novel computational research areas and datasets of interest, through the Allen Institute’s vast data banks. Includes a discretionary fund for each fellow.
  • Participation in the 2-week Summer Workshop on the Dynamic Brain course in the San Juan Islands
  • Mentorship from leading Allen Institute and UW investigators. Fellows are hired as an Allen Institute employee with a starting salary of $106,780 annually, immigration support and benefits package

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.

learn more

shanahan fellowship stories

Arrow Link
news
Making connections
How Yiliu Wang's found her place in neuroscience during the Shanahan Fellowship.
news
Learning how to learn with brains, data and optimization
A Shanahan Fellow’s experience to uncover how the brain multitasks and adapts to the world around it.
news
Sink or Swim: Navigating the deep waters of neuroscience research
Charting a course to understand brain function and neurodegenerative disease through the Shanahan Fellowship.
news
Serendipity and Synapses: How a part-time job unlocked a passion for brain-mapping
For Sven Dorkenwald, Ph.D., mapping the brain's connections was more than a job; it became a passion sparked by a simple twist of fate.

shanahan fellowship publications

view all publications
publication / 2024
Network statistics of the whole-brain connectome of Drosophila
Nature
publication / 2024
Neuronal wiring diagram of an adult brain
Nature
publication / 2024
Beyond expectations: residual dynamic mode decomposition and variance for stochastic dynamical systems
Nonlinear Dynamics
publication / 2024
Hierarchical Bayesian inference to model continuous phenotypical progression in Alzheimer's Disease
bioRxiv
publication / 2024
Information-Theoretic Tools to Understand Distributed Source Coding in Neuroscience
IEEE Journal on Selected Areas in Information Theory
publication / 2023
Gaussian Partial Information Decomposition: Bias Correction and Application to High-dimensional Data
Advances in Neural Information Processing Systems
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meet the fellows

Anamika Agrawal
Scientist I
Matthew Bull
Scientist I - Shanahan Foundation Fellow
Sven Dorkenwald
Shanahan Fellow
Monica Liu
Shanahan Fellow
Lu Mi
Scientist I - Shanahan Foundation Fellow
Ryan Raut
Scientist I - Shanahan Foundation Fellow
Iris Stone
Shanahan Fellow
Maria Tikhanovskaya
Shanahan Fellow
Denis Turcu
Shanahan Fellow
Praveen Venkatesh
Scientist I
Yiliu Wang
Shanahan Fellow
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