Student Edition Issue #257

Connecting underrepresented students in tech with career opportunities

Author

Veni Kunche
August 09, 2026

Hi! Welcome to Diversify Tech's Early Talent Edition! This newsletter is for underrepresented students in tech. Every Sunday, we share jobs, events, and other career opportunities

In this week's edition,
šŸ’¼ The World Bank, MetLife, DoorDash and more are hiring
šŸ“† Tech in Color: Builders' Showcase is on August 19th in D.C.
ā­ļø Scholarship or Travel Fund to attend KubeCon + CloudNativeCon North America

Cheers,
Veni Kunche

JOBS

Jobs found around the web

These companies have not been vetted. Please make sure to do your own research!

Looking for Mid-Senior level roles?

If you have a few years of experience under your belt, our Professional edition will be most relevant to you! We send it every Tuesday.

EVENTS

RESOURCES

  • Scholarship or Travel Fund to attend KubeCon + CloudNativeCon North America: The Dan Kohn scholarship program supports individuals from underrepresented or marginalized groups in tech and open source who want to attend CNCF events like KubeCon + CloudNativeCon North America. Applications are due for the travel funds by September 13. The deadline for the scholarship is October 4th.

  • Computer Science Research Conference Scholarships: ACM-W provides support for undergraduate and graduate students in computer science and related programs to attend computer science research conferences. For research conferences occurring between October 1st to November 30th scholarship applications must be submitted by August 15th.

  • Code the Dreamā€™s free code school is designed to help you become job-ready in as little as one year. Each class is 11-weeks long, completely remote, and requires about 20 hours per week. Deadline for the winter session is November 1st.

  • Dijkstra's Algorithm: Explore the history behind Dijkstraā€™s algorithm and why it became one of the most important ideas in computer science. Youā€™ll see how the algorithm works step by step, using weighted graphs to find the shortest path efficiently.