We are looking for a computational scientist to maintain data analysis pipelines of data of neural activity recorded with prototypes of implantable neural interfaces. The work will initially mostly concentrate on developing algorithms for data analysis and analyzing data sets, but with the development of new closed-loop device prototypes the work will transition to building a software platform enabling real-time closed-loop neural stimulation based on metrics of sensed data. In designing this closed-loop software platform, you will be working closely with electrical engineers that are designing and fabricating custom and closed-loop electrodes for simultaneous sensing and stimulation.
- A Ph.D. degree in Neuroscience or Computational Neuroscience. Experience with scientific computation in Matlab, Python/NumPy, C++ and with applying signal processing, statistics, and machine learning to neural activity data sets. Experience with analysis of local field potential data, EEG data and spike sorting. Experience with electrophysiological experimentation. Published academic research in per-reviewed journals.
In addition, the ideal candidate:
- Possesses attention to detail, superb organizational, documentation, communication, and time management skills. Is an independent and self-motivated individual. Has excellent analytical and problem solving as well as interpersonal skills. Is motivated to help build innovative neural interfaces to diagnose and/or treat neurological diseases.