Image from the labs of S.-H. Roh and S. Wilkens

The world of a cell is a subtle, elegant, and chaotic place. Molecules are crammed closer together than attendees at a rock concert, computers self-replicate with ease, and millions of tiny machines cooperate to build a living city. Imagine yourself, shrunk to the nanoscale, exploring the cell. What might you see? 

We believe that a combination of spatial mental modeling, spaced repetition, and Fermi estimation problems can give motivated learners a useful and beautiful intuition for the cell. In our experience, this intuition is very fun to learn, but requires some activation energy to get past the basics. Therefore, we're making a short (1-2 hour) portal to give autodidacts a running start to the quantitative study of biology.

If you're interested in trying the study materials, email hi@tinymachines.org. You should include a few sentences on why you'd like to try this, and quick notes on your prior experience learning biology or other scientific disciplines. We'll spend an hour teaching you the basics, in exchange for feedback on the experience.

• Who: We're looking for motivated learners. You should be comfortable with basic mental math, but don't need the equivalent of an undergraduate math degree. We'd especially like to work with people who are proficient in a quantitative (non-biology) science or engineering field. 
• When: We'll give you a 1-hour tutorial this week (10/19-10/26), and access to a resource page with our study material (videos, Anki decks, and written problems) in exchange for your feedback.
• What we ask: You'll need an hour of focused, intellectually energized time (so, pick a time that would personally optimize for this).
• Why: Biology thought experiments, to us, are more addictive than a video game and a source of deep joy and beauty. We can't help but want more people to experience this. It may also be useful to build this intuition, but we're probably biased in our assessment of the utility by our enjoyment of the process.

- Laura Deming + Joanne Peng