Lecturer - Computational and Cognitive Neuroscience in Princeton, New Jersey at Princeton University

The Princeton Neuroscience Institute seeks a full-time lecturer to teach courses, and /or teach precepts with an anticipated start date of January 16, 2027. The initial appointment will be through July 1, 2027, and may be renewed at 12-month increments, contingent on satisfactory performance and curricular need. The primary responsibility of the successful applicant will be to teach neuroscience laboratory courses for both undergraduate and graduate students in computational and human cognitive neuroscience. The major objective of these courses is to introduce students to both computational modeling as well as the process of experimental design, execution and analysis using modern methods, including large scale electrode recording, fMRI, EEG, fNIRS, MEG, TMS. The successful candidate may have the ability to teach precepts in other departments, as needed. The successful candidate will also have the opportunity to conduct independent research and publish.

The Lecturer will work with faculty to design and update courses where appropriate. They will be responsible for preparing and presenting lectures, laboratory design and setup, creating/ updating assignments utilizing modern open-sourced Python-based analysis tools, writing and grading examinations, meeting with students outside of class time, monitoring teaching assistants, and assigning grades.

Essential Qualifications: Ph.D. in neuroscience or related fields (such as computer science, math or engineering) with a specific focus on relevant applications in computational and human cognitive neuroscience. Proficiency with Python and Jupyter Notebooks. Must have an understanding of mathematical and computational tools used for computational modeling of, and analyzing, behavioral and neuroscientific data. Preferred Qualifications: Experience in teaching at the undergraduate and graduate level. Familiarity with machine learning.

Applicants should submit a cover letter, curriculum vitae, teaching statement and contact information for three referees via Interfolio. Preference will be given to candidates who apply by November 30, 2026. This position is subject to the University's background check policy.

We seek faculty members who will create a climate that embraces excellence and diversity, with a strong commitment to teaching and mentoring that will enhance the work of the department and attract and retain a diverse student body, both at the undergraduate and graduate levels.