Shanahan Foundation Fellowship at the Interface of Data and Neuroscience

Shanahan Foundation Fellowship at the Interface of Data and Neuroscience is sponsored by Shanahan Foundation (administered by the Allen Institute and University of Washington). This three-year fellowship supports exceptional early-career scientists from diverse fields at the interface of data and neuroscience, providing funding and mentorship to accelerate contributions to open, large-scale discovery.

Shanahan Foundation Fellowship | Allen Institute careers and opportunities sharing science to speed discovery discovery is a team effort their input shapes our science they help us fulfill our mission shanahan foundation fellowship at the interface of data and neuroscience contributing bold ideas to redefine discovery fostering emerging leaders in bioscience science at the scale of greatest impact sharing science to speed discovery building a blueprint of the brain understanding how cells become organs revealing the brain’s hidden algorithms creating the ultimate immune system reference seattle hub for synthetic biology accelerating human brain research and disease therapeutics unlocking new frontiers of bioscience revealing the mechanisms behind movement and learning sharing science speeds discovery real science.

real skills.

experience science where it happens the human stories behind discovery public engagement, workshops, seminars and more sharing science to speed discovery 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 .

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."

shanahan fellowship applications Applications for Fall 2027 will open September 15th and close December 1st, 2026 . Selected candidates will be invited to give virtual talks on February 1st and 2nd, 2027 . A subset of those candidates will then be invited for in-person interviews on March 1st and 2nd.

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 $111,100 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.

shanahan fellowship stories finding Alzheimer's targets, one cell type at a time How Shanahan Fellow Iris Stone used her Alzheimer's research and business savvy to chart a path into biotech developing AI models that learn like a real brain Shanahan Fellow Denis Turcu is using the world's most detailed brain map to rewrite how machines learn How Yiliu Wang's found her place in neuroscience during the Shanahan Fellowship.

shanahan fellowship publications Evidence from spatial transcriptomics for the mosaic hypothesis and pure cell types in the cortex Arousal as a universal embedding for spatiotemporal brain dynamics CAVE: Connectome Annotation Versioning Engine Integrated multimodal cell atlas of Alzheimer's disease Whole-brain annotation and multi-connectome cell typing of Drosophila The fly connectome reveals a path to the effectome shanahan fellowship alumni Iris Stone, Ph.

D. (2023-2026) | Neuroscientist III, External Scientific Programs, Beacon Biosignals Sven Dorkenwald, Ph. D.

(2023-2025) | Assistant Professor, McGovern Institute and the Department of Brain and Cognitive Sciences at MIT Ryan Raut, Ph. D. (2021 – 2024) | Instructor in Radiology, Washington University School of Medicine in St.

Louis Anamika Agrawal, Ph. D. (2022 – 2025) | Weill Neurohub Fellow, University of Washington Praveen Venkatesh, Ph.

D. (2021 – 2024) | Research Scientist, UpStart Matthew Bull, Ph. D.

(2022 – 2025) | Technical Staff, AI Theory, Unconventional AI​ Monica Liu, Ph. D. (2021 – 2024) | Staff ML Scientist – Precision Neuroscience​ Lu Mi, Ph.

D. (2022 – 2024) | Assistant Professor, College of AI at Tsinghua University we accelerate develop catalyze impact science done differently . shared openly.

Mapping every cell, connection, and circuit in the brain—openly shared with the world. Decoding how cells become tissues, then programming that knowledge into powerful new research tools. Revealing the brain's hidden algorithms that transform neural activity into real-world behavior.

Creating the deepest open reference for the healthy human immune system ever built. Engineering cells to record their own histories, transforming how we understand disease over time. Advancing evolution to explore biology’s full design space and advance human health Accelerating human brain research and new therapeutic strategies for neurological conditions Big questions, open answers, and science built to be shared.

Inspiring the next generation of scientists through open science resources. Our science is empowering researchers and advancing health worldwide.