Postdoc in Neural Dynamics & Control Theory

Phase2 Technology; Tucson (AZ); On-site; USD 55,000 - 70,000; Full time

Benefits offered by this job

Health insurance

Tuition reduction (UA/ASU/NAU)

Paid vacation & holidays

Job summary

University of Arizona's Maurer laboratory seeks a Postdoctoral Research Associate in neuroscience to develop theoretical and computational approaches for understanding how inhibitory circuitry shapes neural dynamics and state space trajectories. Collaboration with experimentalists and access to rich electrophysiological datasets will guide mechanistic predictions tested via interventions.

The ideal candidate holds a PhD in a quantitative field and has strong programming skills

Qualifications

• PhD or equivalent doctoral degree by start date.
• Experience with mathematical modeling, computational analysis, dynamical systems, or control.
• Proven ability to conduct rigorous independent research.

Responsibilities

• Develop mathematical, computational, and/or control-theoretic models of recurrent neural dynamics and inhibition constraints.
• Analyze large-scale electrophysiological and behavioral datasets and connect predictions to neural activity.
• Use perturbations to distinguish models and identify governing variables.
• Investigate stability, metastability, attractor structure, controllability, and state transitions.
• Collaborate with experimental neuroscientists to design analyses and tests of predictions.
• Present findings at meetings and contribute to publications.

Skills

Quantitative reasoning

Nonlinear dynamics

Control theory

Scientific programming (Python/MATLAB/

Independent researcher

Education

PhD or equivalent doctoral degree in engineering, applied mathematics, physics, computational neuroscience, computer science, quantitative biology, or related discipline

Tools

Python

MATLAB

Julia

C/C++

Job description

University of Arizona's Maurer laboratory seeks a Postdoctoral Research Associate in neuroscience to develop theoretical and computational approaches for understanding how inhibitory circuitry shapes neural dynamics and state space trajectories. Collaboration with experimentalists and access to rich electrophysiological datasets will guide mechanistic predictions tested via interventions.

The ideal candidate holds a PhD in a quantitative field and has strong programming skills