Join us

Postdoctoral scholars

We are recruiting postdoctoral scholars to work at the interface of machine learning, control theory, and neuroscience through multi-institutional NIH and DoD projects.

The work develops methods to model and decode brain network activity, and to control this activity with electrical or optogenetic stimulation. Projects study the neural dynamics underlying movements in nonhuman primates and mood states in humans, and develop closed-loop neurotechnology in humans.

Research opportunities

Postdoctoral scholars can lead interdisciplinary work with collaborators in electrical engineering, computer science, and neuroscience across multiple academic institutions.

• Model-based neural control. An NIH R01 project develops control of electrical brain stimulation for mood and mental disorders, with testing in human participants with intracranial electrodes in collaboration with Edward Chang’s Lab at UCSF.
• Nonlinear neural dynamics. An NIH New Innovator Award (DP2) project develops geometric nonlinear dynamical models and decoders of neural population activity, studying motor and cognitive tasks in human and nonhuman primate datasets.
• Multiscale modeling and brain-computer interfaces. MURI and BARI DoD projects develop machine learning methods for multiscale neural recordings and non-invasive EEG brain-computer interfaces for enhanced decision accuracy. Collaborators include UC Berkeley, Duke, Harvard, NYU, UCLA, Imperial, UCL, and Essex.

Qualifications

Applicants should hold a PhD in electrical engineering, computer science, applied mathematics, statistics, physics, or a related field. A neuroscience background is helpful but is not required.

Applying

Postdoctoral applicants should email Professor Maryam Shanechi and include a CV.

About the lab

Based in USC Viterbi’s Department of Electrical and Computer Engineering, our lab is also part of the Neuroscience Graduate Program and Biomedical Engineering. We model, decode, and control neural dynamics to study the brain and develop neurotechnology. Collaborations with human and nonhuman primate neurophysiology labs connect computational work with neural recordings and electrical or optogenetic stimulation.

Graduate students

We are recruiting PhD students with a strong mathematical background.

We welcome candidates interested in developing machine learning, signal processing, and control-theoretic algorithms for neural engineering and neuroscience applications.