이 에피소드에 관해
Most bench scientists think breaking into computational biology means going back to school. Dean Lee proves otherwise. Dean went from neuroscience PhD student at Harvard to Principal Computational Biologist at Novartis by teaching himself to analyze scRNA-seq data in stolen scraps of time alongside his bench job, and now he helps thousands of scientists make the same move through his online community Dean's List.
In this episode, Dean and Carina break down exactly what it takes to build real computational biology credibility without another degree, without quitting your job, and without waiting for someone to hand you permission.
You'll learn:
- Why Coursera certificates don't move hiring managers and what actually does
- How to find public biological data and build your first comp bio project this week
- The reproducibility strategy: why re-analyzing a published Nature paper is an industry skill and your best portfolio move at the same time
- How to pitch yourself as a funded intern through the Massachusetts Life Sciences Center to break into small biotech startups
- The state of entry-level comp bio hiring in 2026 and where the openings actually are
- How to frame volunteer work and self-directed projects on your resume so hiring managers take them seriously
Whether you've been thinking about this pivot for years or you're just starting to wonder if it's possible, this conversation gives you the roadmap.
- RNA-Seq and ScRNA-Seq Courses
- How to become a computational biologist in a year
- The Big Challenge... With Dean Lee
- Dean's List
- Link In with Dean!
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00:00 Dean Lee's path from Harvard neuroscience to computational biologist at Novartis
04:00 The volunteer scRNA-seq project that launched Dean's career pivot
07:30 Why hiring managers ignore certificates and look only for project work
12:00 How reproducing published research builds irrefutable portfolio proof
21:30 The MLSC funded intern hack for breaking into biotech startups
26:30 The 2026 comp bio job market and where entry-level roles actually exist
30:00 How to transition into computational biology within your current company
33:00 Operational AI vs scientific AI and what it means for your comp bio career
