This programme funds pre-doctoral researchers (undergraduate and post-baccalaureate) to gain hands-on research experience in computational neuroscience at the University of Washington and Allen Institute. It exists to train the next generation of computational neuroscientists by providing mentorship, interdisciplinary collaboration, and support for publishing/presenting work.

- Eligibility: Must be a current student or recent graduate (undergraduate or post-baccalaureate); pre-doctoral status required. - Research fit: Interest and background in neural computation, neural networks, computational modeling/method development. - Mentorship potential: Ability to work with a Shanahan Postdoctoral Fellow and researchers at UW and Allen Institute. - Diversity and inclusion: Likely considers underrepresented groups, including LMIC candidates. - Academic record: Transcripts and CV reviewed for relevant coursework, research experience, and skills. - Cover letter: Must articulate motivation, fit with available projects, and career goals in computational neuroscience.

Past cohorts include recent graduates and current undergraduates from US and international institutions, often with backgrounds in neuroscience, computer science, physics, or engineering. Named examples not found on page, but typical profiles include students with prior research in neural data analysis, modeling, or machine learning, and strong letters of recommendation.

A recent graduate or current undergraduate with a strong foundation in computational methods (e.g., Python, modeling, data analysis) and neuroscience, eager to work on interdisciplinary projects at UW/Allen Institute. The ideal applicant demonstrates research maturity, clear career goals in computational neuroscience, and ability to thrive in a mentored, collaborative environment.