Wet, dry, and humanities labs each read outreach differently. Match the tone of your email to the kind of work the lab actually does.
Wet Lab — Biology, Chemistry, Life Sciences
Bench work, lab techniques, and in-person hours dominate the conversation.
What makes this lab type different
- •Hands-on training is required before independent work — expect an onboarding period.
- •Time commitment is real: 10-15+ hours per week is a typical minimum.
- •Safety training and lab notebook discipline matter from day one.
- •Undergrads often work under a graduate student or postdoc mentor.
Skills to highlight
- •Specific lab techniques (PCR, cell culture, microscopy, sterile technique, Western blot).
- •Completed lab courses by name (e.g. MCBT 310, CHEM 233) — not just the department.
- •Realistic weekly hours you can actually commit, including in-person.
- •Computational adjuncts (ImageJ, GraphPad Prism, basic R or Python).
Common mistakes
- •Don't overstate technique experience you've only read about.
- •Don't lead with a GitHub link — wet PIs care about bench reliability.
- •Don't underestimate the hours commitment.
Dry Lab — CS, Engineering, Data Science
Skills, projects, and a real GitHub link are worth more than a list of buzzwords.
What makes this lab type different
- •Skills-focused hiring: PIs care most about what you can already build.
- •More flexible schedules; remote work is sometimes possible.
- •Project-based: you may be assigned a specific tool or paper to extend.
- •Some labs use a short technical screen before onboarding.
Skills to highlight
- •Programming languages that match the lab's stack (Python, C++, JavaScript, R).
- •A recent project with a real GitHub link and a short README.
- •Specific technical interest (ML, CV, NLP, systems) — not just "AI".
- •Familiarity with Git, Linux, and at least one ML framework if relevant.
Common mistakes
- •Don't list skills without evidence — link a project.
- •Don't say "I'm interested in AI" — be specific about which subfield and why.
- •Don't ignore the lab's tech stack (TensorFlow vs PyTorch vs JAX).
Humanities Lab — Social Sciences, Arts, Humanities
Often called RA positions. Writing, research methods, and genuine intellectual curiosity matter most.
What makes this lab type different
- •Most positions are research assistantships ("RAs") rather than "lab seats".
- •Structures vary: some have grad students, some are 1-on-1 with the professor.
- •Human subjects research requires ethics training (often IRB).
- •Strong writing is highly valued for literature reviews and qualitative work.
Skills to highlight
- •Research methods (qualitative coding with NVivo, survey design with Qualtrics, archival research).
- •Writing strength — literature reviews, academic writing courses, citation management (Zotero).
- •Quantitative skills if relevant (SPSS, Stata, R).
- •IRB / human-subjects training certificates if you have them.
Common mistakes
- •Don't write a generic "I'm interested" email — humanities PIs spot it instantly.
- •Don't focus only on grad-school prep — emphasize what you can contribute now.
- •Don't undervalue "soft" skills like writing and attention to detail.