Machine learning for R&D: From hot topic to practical application
As much as we hear about ML, not many are taking advantage of it in their scientific work. By delivering ML-driven functionality for targeted use cases, modern software can turn the theoretical into practical tools.
This presentation focuses on two use cases: protein structure prediction and strain parameter optimization. We’ll highlight how Benchling makes these tasks more efficient, and highlight the impact of customers currently taking advantage of ML as part of this everyday work.
Head of Data & Analytics Product Management at Benchling