Skills for Research at the SAGE Lab
There is no single profile required to join the SAGE Lab. The skills below are useful directions for students and collaborators who want to contribute to rigorous, open, and practically meaningful research. They can be developed gradually through courses, independent projects, community activities, and research experience.
Data analysis and data wrangling
Learn to work carefully with real, messy data: importing and documenting data, checking quality, reshaping tables, handling missing values, visualizing patterns, and choosing analyses that match the research question. We primarily use the open-source language R, including the easystats ecosystem and related tools.
Programming and research tools
Programming makes research more reproducible and allows useful ideas to become tools that others can inspect and use. Useful projects include R Markdown or Quarto reports, data dashboards, Shiny apps, websites, simulations, and scripts that automate repetitive work. The goal is not to write code for its own sake, but to make reasoning, analysis, and communication clearer and more reliable.
Scientific writing
Strong research requires clear, precise writing in English. Students should develop the ability to explain a question, build an argument from evidence, describe methods accurately, acknowledge uncertainty, and revise carefully. For people who want to publish internationally, high-level scientific English is an important part of preparing work for selective, high-impact journals.
AI and autonomous agents
AI tools and autonomous agents can support quality checks, programming, analysis, literature work, and presentation. The essential skill is using them expertly and critically: writing precise requests, checking sources and code, testing outputs, protecting confidential information, recognizing fabricated or biased results, and taking responsibility for the final work. A plausible AI-generated answer is a starting point for verification, not evidence that the work is correct.
Funding and project development
Research depends on resources, including participant compensation, software and infrastructure, research assistance, travel, and time. Students and collaborators should learn to identify scholarships, fellowships, grants, and other funding opportunities; develop a focused project; write a convincing proposal; and explain why the work matters. Successful independent funding can substantially improve the feasibility of joining a project at the SAGE Lab.
How to start
Choose one small project and make it concrete: reproduce an analysis from an open dataset, write a short report in R Markdown or Quarto, build a simple visualization or dashboard, draft a research question, or identify a funding opportunity and study its requirements. Sharing progress with peers through the SAGE Community can make the learning process more useful and more enjoyable.
These skills are goals, not a checklist or a promise of a research position. They help people make meaningful contributions and make it easier to match an opportunity with the time, preparation, supervision, and funding available.