The Maurer laboratory in the Department of Neuroscience at the University of Arizona is recruiting a postdoctoral researcher interested in theoretical and computational approaches to neural dynamics. A central question is how inhibitory circuitry reshapes the states and transitions available to a recurrent neural network: not simply by reducing excitation, but by dynamically restricting, routing, and stabilizing trajectories through neural state space. We are particularly interested in whether relatively low-dimensional inhibitory or feedback signals can reorganize high-dimensional population activity, alter attractor structure and metastability, regulate transitions among network states, and stabilize circuits that would otherwise be unstable or chaotic. The position sits deliberately between theory and experiment. The researcher will have access to large-scale electrophysiological datasets including neuronal spiking, LFP, EEG, behavior, and circuit perturbations. The goal is to develop mechanistic models that generate discriminating predictions and can be tested against experimental interventions, rather than simply fitting models to neural data. We welcome applicants from computational neuroscience as well as control theory, nonlinear dynamical systems, applied mathematics, engineering, physics, computer science, and related quantitative fields. Prior neuroscience experience is not required. The position is full-time at the University of Arizona in Tucson, with salary according to NIH guidelines and full benefits. Applications are open until the position is filled. University of Arizona posting: req27102 Application materials: CV, cover letter, and statement of research interest. For informal questions, please contact: Andrew P. Maurer, PhD Associate Professor, Neuroscience University of Arizona drew@arizona.edu