I'm a machine learning and have done work with Bayesian methods for modeling dynamic systems. I've been considering jumping into a synthetic biology company in industry. I've been searching for statistics and machine learning problems that need solving in synthetic biology. I suspect that there are two problems where a statistician or machine learning expert could contribute. The first is building data-driven models of metabolic pathways. The second is implementing an active learning approach to organism design -- basically building a robot that iteratively conducts experiments that maximize information while minimizing cost. But I also suspect that synthetic biology companies like yourself and Zymergen are more concerned with scaling up your business in the short term, and that implementing machine learning or computational biology-types of processes is a long term "optimization" task, not important to the core business in the near term. I'm afraid of making the jump if this type of work isn't important to the organization. Can you please comment? Cheers.