Long-Term Email Scraping

GOAL: extract emails for (every or most) colleges students at 500+ specific universities and colleges in America. We're aiming to apply a similar process across approximately 500 colleges and universities. The workflow outlined below for Yale University serves as an example to illustrate the approach. However, we're flexible and open to exploring alternative workflows if you believe they could be more effective, efficient, or feasible—feel free to suggest modifications or entirely different methods based on your expertise. Example Workflow for Targeting Yale University Students' Emails LinkedIn Search for Granular Targeting: Conduct searches on LinkedIn using queries like "Yale University Class of 2026", "Yale University Class of 2027", "Yale University Class of 2028", and "Yale University Class of 2029" to identify current students across these four class years. Name Scraping and Verification: Scrape as many names as possible from the LinkedIn search results. Build and use an agent to verify that the individuals are indeed current students. Email Identification: Use available tools to locate emails based on the scraped names. Leverage university directories (e.g., similar to https://directory.brown.edu/ for other institutions) where available. As a fallback, research and deduce the university's email format online. This example approach sounds effective for targeted outreach. Most of the process (searching, scraping, verification, and email lookup) is intended to be handled through autonomous systems. Apply tot his job