Lab Culture

At CTML, we value a lab culture that is collaborative, supportive, inclusive, open, and free from discrimination and harassment. We believe that our lab thrives when all members feel safe and respected in sharing their ideas and opinions. Therefore, we encourage students and staff of all experience levels to respectfully share their honest opinions and ideas on any topic. If you feel confused or unsure about anything, including expectations, the collaboration process, your research, or communication with external funders or collaborators, please communicate with your advisor or other members of CTML.

Diversity, Equity, and Inclusion

The CTML is committed to cultivating a culture of diversity, equity, and inclusion. We aim to be a safe, supportive, and anti-racist environment in which students from diverse backgrounds are equally and inclusively supported in their education and training. We recognize that diversity takes many forms, including differences in race, ethnicity, gender, sexuality, socioeconomic status, religion, disability, and political affiliation. We strive to create an environment where all members feel valued and respected.

Protecting Human Subjects

At CTML, we take the protection of human subjects in research very seriously. All lab members working with human subjects data should complete CITI Human Subjects Biomedical Group 1 training and share their certificate with Andrew Mertens. Before starting work on any project, Andrew will add team members to relevant Institutional Review Board protocols to ensure they have permission to work with identifiable datasets.

Confidentiality is one of the most important aspects of protecting human subjects in our work. As a student supporting our data science efforts, you should:

• Understand and comply with project-specific policies about where data can be saved, particularly if the data include personal identifiers.
• Not share data with anyone without permission, including other members of the group who might not be on the same IRB protocol as you (check with Andrew first).
• Do not download identifiable data to your personal laptop or other computers, and make sure you are storing the data in a protected location allowed by the UCB IRB board (examples: Berkeley Box, Savio, or private servers like the Hubbard lab’s RedVelvet server.
• Talk to your supervisor if you have any concerns about proper practices.

Remember, data that looks like it does not contain identifiers might still be classified as data that requires special protection by our IRB or under HIPAA. Always proceed with caution and ask for help if you have any concerns about how to maintain study participant confidentiality.

We hope that this guide provides you with a helpful overview of the culture, policies, and procedures that are important to our lab. If you have any questions or concerns, please do not hesitate to reach out to Andrew or any other member of the lab.