LUMeN Lab
For Prospective PhD Students

For Prospective PhD Students

The LUMeN Lab will be considering applications this cycle for graduate student enrollment in Fall 2025!

Prospective students are strongly encouraged to carefully review the lab website and recent publications on which Dr. Cohen is first, second, or last author prior to applying to gauge potential fit. Potential students should follow application instructions provided by the Department of Psychology and Laney Graduate School (learn more about a need-based waiver of application fees to Laney Graduate School here). Due to the number of applicants, individual conversations with prospective students generally do not occur until after applications are submitted, at which time top candidates are invited for an initial phone interview. For more information about our lab culture and expectations, click here.

We are looking for diligent students with strong interests at the intersection of affective, computational, and developmental cognitive neuroscience. Prospective lab members should be interested in working on multiple levels of analysis (e.g., behavior, psychophysiology, neuroimaging) in order to understand basic motivated learning and memory mechanisms.

Most competitive applicants typically have:

  • Completed an independent research project and/or made substantial intellectual and technical contributions to research projects.

  • Achieved an intermediate-level or higher proficiency with at least one statistical computing language (e.g., Matlab, R, or Python) and are able to describe how they have used it to test a hypothesis.

  • Experience working as a full/part-time research assistant or lab manager in their post-bac years.

  • Strong organizational and communication (verbal and written) skills.

In your application, be sure to highlight your research skills (especially those pertaining to study design, data collection, data analysis, and presentations/manuscript preparation) and research experience, as these are often weighted most heavily in determining top candidates.