Computational Neuroscience Postdoc: Neural Dynamics

The University of Arizona; Tucson (AZ); Sur place; USD 65 000 - 90 000; Plein temps

Avantages offerts par ce poste

Health insurance

Vacation & sick leave

Tuition reduction

Recreation & culture

Résumé du poste

University of Arizona seeks a Postdoctoral Research Associate in Neuroscience to develop theoretical and computational approaches for understanding how neural networks organize activity through nonlinear dynamics and feedback. The role emphasizes inhibitory control and state-space routing to stabilize trajectories and enable flexible computation.

The candidate will collaborate with experimental neuroscientists, access rich datasets, and aim to produce mechanistic, testable predictions tested

Qualifications

• PhD or equivalent doctoral degree by the start date.
• Demonstrated experience in mathematical modeling, computational analysis, dynamical systems, control, or a closely related area.
• Evidence of the ability to conduct rigorous independent research.

Responsabilités

• Develop mathematical, computational, and/or control-theoretic models of recurrent neural dynamics, with emphasis on how inhibition and feedback constrain reachable network states and transitions.
• Analyze large-scale electrophysiological and behavioral datasets and connect model predictions to neuronal spiking, population activity, LFPs, EEG, and behavior.
• Use experimental perturbations to distinguish among competing mechanistic models and identify governing variables.

Connaissances

Quantitative reasoning

Mathematical modeling

Scientific programming

Independent research

Formation

PhD or equivalent

Outils

Python

MATLAB

Julia

C/C++

Description du poste

University of Arizona seeks a Postdoctoral Research Associate in Neuroscience to develop theoretical and computational approaches for understanding how neural networks organize activity through nonlinear dynamics and feedback. The role emphasizes inhibitory control and state-space routing to stabilize trajectories and enable flexible computation.

The candidate will collaborate with experimental neuroscientists, access rich datasets, and aim to produce mechanistic, testable predictions tested