Scientist I – Neural Circuits Theory

The goal of the Neural Dynamics accelerator is to understand how the brain generates flexible behavior. We aim to uncover the algorithms—implemented by dynamics in brain-wide neural circuits—that allow animals to build internal models, process information, and choose actions.

We are searching for a Scientist to develop data-driven theories of how circuit structure shapes neural computation. The Scientist will use the Institute's large-scale connectivity atlases and brain-wide recordings to understand how the brain's wiring organizes neural dynamics and drives flexible behavior. The position offers a rare opportunity: distilling theories of computation from connectivity data produced at unprecedented scale, together with spike trains from thousands of neurons recorded simultaneously across multiple brain regions, and a wealth of targeted activity perturbations during behavior.

The ideal candidate has deep expertise in applied mathematics or statistical physics, fluency in modern machine learning for science, and a genuine interest in how the brain computes. The role requires close collaboration with experimentalists using state-of-the-art anatomical, electrophysiological, and imaging methods. The goal is to make fundamental discoveries about how mammalian circuit architecture gives rise to function, and to generate insights that shape new experiments at the Institute.

PhD in neuroscience, physics, applied mathematics, statistics or related field; or equivalent combination of degree and experience

Demonstrated ability to build theories of collective dynamics in systems of many interacting elements

Strong scientific-computing skills and familiarity with modern machine learning
Primary work location is Seattle; any remote work must be performed in Washington State.