Rockefeller University

Research Assistant | Laboratory of Neural Systems

Job Locations US-NY-New York
Position Type
Regular Full-Time

Organization Overview

Our visual perception of the outer world is the creation of active brain processes that structure and select the information provided by the eyes. The Laboratory of Neural Systems is interested in the neural processes that form object representations as well as those that allow attention to make those representations available for cognition. Our laboratory aims to understand the inner workings of this system,from the level of individual cells to the interactions of brain areas,in order to answer questions such as: How does face selectivity emerge in a single cell? How is information transformed from one face patch to another? What is the contribution of each face patch to different face recognition abilities,like the recognition of a friend or a smile? How do the different face patches interact in different tasks? And how is information extracted from a patch when a perceptual decision is made?


The Laboratory of Neural Systems is looking for a highly motivated student with an excellent academic background interested to work on a cutting-edge interdisciplinary neuroscience project on the foundations of the neural basis of compositionality, or the ability to generalize from a small set of rules to a large set of complex behaviors, which is currently unknown. We have developed a new experimental paradigm to discover these neural mechanisms. This paradigm combines a new behavioral task, large-scale neural recordings, and computational modeling. The project involves close collaborations with two leading computational labs, one on computational neuroscience at NYU (Xiao-Jing Wang), and another on artificial intelligence at MIT (Josh Tenenbaum). The RA will work closely with an enthusiastic postdoc in the lab (Lucas Tian), and will have many opportunities to engage in the cross-institute collaboration. The RA will design, implement, and analyze results for NHP behavior. The RA will perform large-scale neural recording studies. The RA will build and test computational models of this behavior (e.g., neural networks). The RA will, under proper guidance, present results at scientific meetings, and is expected to co-author a scientific paper. The RA will develop cutting-edge skills at the intersection of neuroscience, computational cognitive science, and artificial intelligence, and will be in a great position to enter and succeed in an excellent graduate program in any of these fields. A commitment of 2 years is expected.


Responsibilities include:

  • Running and recording NHP behavioral studies

  • Analysis and computational modeling of neural and behavioral data

  • Various animal-care tasks 

  • Presenting and writing up results in lab and scientific meetings

  • Producing figures for an upcoming publication

  • Other tasks related to the project as needed



  • Bachelor's degree in Biological Sciences or a related field
  • Above all, curiosity and eagerness to learn

  • Good communication, organization, and people skills

  • Excellent work ethic


  • Basic knowledge of programming or motivation to learn (e.g. MATLAB, Python)


The Rockefeller University does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy, gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service or other non-merit factor. All qualified applicants will receive consideration for employment without regard to the characteristics listed above.


The salary of the finalist selected for this role will be set based on various factors, including but not limited to organizational budgets, qualifications, experience, education, licenses, specialty, and training. The hiring range provided represents The Rockefeller University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Compensation Range: Min

USD $48,300.00/Yr.

Compensation Range: Max

USD $52,000.00/Yr.


Sorry the Share function is not working properly at this moment. Please refresh the page and try again later.
Share on your newsfeed