We are always looking for passionate engineers to join us to tackle tough challenges. Just because something isn't doable today doesn't mean we can't shoot for the moon! There's no better place to change how biology is engineered than here. Ping us if you are interested in joining our efforts.
If I'm interested in this technology how do you recommend learning the required techniques. As a machine learning engineer I know maths more then biology, but want to contribute to the open source movement. Where do you view the biggest impact of software/machine learning engineers can make to the open sourced biology movement?
In terms of SB as a career, the field is moving so fast it's better to focus on problem solving than techniques. Cloning will be obsolete soon; how would you design biological systems when you can synthesize any DNA sequence you want?
Do you foresee synthesis costs falling quickly? It seems like its a major factor holding back commercial applications of synthetic biology.
Congrats on the funding and best of luck as you continue to scale!
I applied with my partner with a similar goal a couple of years ago, and was rejected. The criteria for biotech applications was very vague then, and we tried to keep our pitch as non technical as possible which I think worked against us.
Also, do you have an in house gene design method or do you rely on the supplier to optimize? As I see it, the two major obstacles are reaching commercially viable expression yields, and identifying market demand.
That last line about Twist delivering 400 base pairs has to be wrong, right? Do they mean 400 million?
Will there be synthetic probiotics in the future? (I understand that some probiotics are already heavily engineered.)
