Seeking a postdoctoral fellow in the Department of Cognitive Science to analyze naturalistic MEG data focused on cross-linguistic mechanisms of human sentence processing, starting July 1, 2026. The role involves preprocessing and analyzing SQUID MEG data using tools like MNE-Python or FieldTrip, applying source localization and temporal response function analyses, and working within a collaborative research environment.
Required qualifications include a PhD in cognitive science or related fields, experience with MEG data analysis, programming skills, and knowledge of machine learning, statistics, and linguistics. Preferred skills encompass expertise in neurolinguistics, neural language models, and interest in oscillatory/connectivity dynamics during language comprehension.
Salary is $62,232/year. Applicants should submit a CV, research statement, and references via Interfolio. The position is full-time with benefits, and the university is an equal opportunity employer. Pre-employment background checks and vaccine requirements apply.