Lab Philosophy & Opportunities

What do we value as a lab outside of research?

• Regardless of the specific research questions we are trying to answer, we strive to maintain the highest level of scientific integrity, as well as making our science open and reproducible.

• Diversity, equity and inclusion: the lab should be a safe space in which every member belongs and thrives.

• Mentorship and career support: whatever any lab member wants to achieve beyond their stay in the lab, we help each other and share resources to make it happen!​

• Mental well-being and work-life balance: we all have a life beyond the lab, which we should value and intentionally take time for, whether it’s hobbies, friends, family, sports, traveling or just alone time!

What are opportunities to join the lab?

Read below for some opportunities to get involved and don't hesitate to reach out!

• The lab will be reviewing applications for PhD admission for Fall 2027. Note that we are not yet approved for recruiting a student, so our ability to make an offer will depend on funding available within the department (TAship) and external (grants). Applications will be reviewed from the following two programs: Program in Neuroscience and Cognitive Science and the Department of Psychology - CNS area (with a slight preference for NACS). Other tips:

  • We are particularly interested in candidates with a strong interest in social learning, its neuro-cognitive mechanisms, and its relationship to mental health, as well as deploying computational methods, improving the ecological validity of social neuroscience paradigms, and tuning into open science and reproducibility practices.

  • In preparing your research statement, make sure to detail your specific research interests and why our group would be a good fit for your training and development of those research interests.

  • Feel free to reach out by email to Caroline (ccharpen@umd.edu) if you intend to apply and/or have questions - but note that depending on the volume of applications, answers may be delayed. We also won't be able to schedule a call or zoom meeting with you before the application deadline, out of fairness for all applicants.

• Student research assistant: if you are an undergraduate or master’s student interested in joining the lab part-time for research credits or as a summer volunteer/intern, please fill out this Student RA interest form, and we will reach out if your application matches some of our ongoing projects! 

• Visiting graduate student: Master’s students hoping to complete their Master’s thesis (remote supervision is also an option) or visiting PhD students who would like to collaborate on a project and experience a different lab environment for a few months. To discuss these opportunities, please reach out at ccharpen[at]umd[dot]edu with your CV and a summary of your research interests.

Additional resources and useful information

For graduate school applicants:

• Application Statement Feedback Program: https://www.asfp.io/ - get feedback on your research/personal statements.

• Check here if you qualify for an application fee waiver at UMD. 

Computer Programming skills:

• The best Python bootcamp, by Justin Bois.

• Twitter thread of resources to learn R as a psychologist.

• Good coding practices: The Good Research Code Handbook, by Patrick Mineault.

Readings and Tutorials on Computational modeling:

• See this document for detailed resources if you are looking to learn about computational modeling, both theoretically and practically.

Funding opportunities:

• Up-to-date repository of early-career funding opportunities (mostly relevant for postdocs)

How do/should we use AI in the lab?

• In June 2026, the lab met and discussed generative AI use in the lab and for research more generally. A lab AI use policy was drafted as a result, with 5 guiding principles:

  1. AI does not do your learning or thinking for you

  2. You are responsible for what you produce

  3. Protect data and privacy

  4. Match your investment in AI tools to your work, not the other way around

  5. Be transparent about how you used AI tools

• The detailed current version policy, as well as tips and resources, can be found here.