Brain Prosthesis Algorithms
Brain science is the new rocket science.
We’re building algorithms and software to correct deficits and enhance cognitive brain function using electrophysiology. We’re not making drugs or creating a brain training game, we’re using a data driven method to create neural prostheses to restore and enhance human cognitive performance. Join us in this delicious engineering opportunity in developing probabilistic kernel models of the hippocampus for a first application in memory.
What we’re looking for: a data & algorithms or machine learning specialist with an exceptional aptitude for regularization and matrix algebra. Potential projects include building classification and regression models for neural spiking data, decoding of the spatio-temporal patterns of spikes with respect to behavior, analyzing large-scale complex neural data, building mixed model of point-process signals, and other data-driven modeling projects. Working with the cross-disciplinary members of our team which includes Professors at the University of Southern California (USC), you would be driving a neural system identification modeling platform that is pushing the state-of-the-art in neurocognitive therapeutics.
Self-taught or via formal education, we expect not only that you meet our prerequisites on skills and mission alignment, but that you thrive in a meritocracy of mutual peer review within a first-class team. We expect that you take responsibility for your projects, demonstrate excellence, vision, and diligent but creative invention.
You are the right person for this job if you are:
Strong in linear algebra/matrices, basis transformations, model order / dimension reduction, numerical methods
Strong in regression analysis, data analysis, nonlinear mathematical modeling
Results oriented, driven, flexible, adaptable, and have the courage to take on an ambitious project, because what matters most is to build a flourishing future
We’d also love it if you have skills and experience in:
Either electrical engineering, biomedical engineering, statistics, computer science, computational neuroscience, or related fields
Machine learning (e.g. Bayesian, deep learning), time series analysis, pattern recognition, and point-process signal processing is highly preferred
Neural circuit modeling / exploration (e.g. discovering functional connectivity), control theory, system identification, compartmental neural modeling (e.g. NEURON)
Python, Matlab, C/C++/C#, R, Linux/Unix
Exceptional team. Full-time. Benefits. Competitive compensation. Ground breaking work.