Machine learning lies at the core of insitro’s approach to rethinking drug development. As part of the small molecule machine learning group, you will lead the development of cutting edge machine learning methods that solve key problems in the drug development process. You will work in cross-functional teams whose members span drug-discovery, high-throughput biology and chemistry, machine learning, and data engineering. Your job will be to deeply dive into creating and understanding molecular and DNA encoded library datasets, defining rigorous data splits, developing novel molecular featurization and modeling recipes, and integrating information from differing sources to deliver production quality ML models that can rapidly accelerate therapeutic programs. You will work as part of a team to solve problems in improving protein-drug binding affinity whilst avoiding toxicity issues and minimizing off-target interactions. Along the way, you will learn a broad range of scientific, mathematical, and engineering skills, receive close mentoring from senior scientists and engineers, guide and mentor junior scientists and engineers, build lasting relationships with your colleagues, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!
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Benefits at insitro
insitro is a data-driven drug discovery and development company using machine learning and data generation at scale to transform the way that drugs are discovered and delivered to patients. insitro’s approach focuses on the development of predictive machine learning models to be brought to bear on key bottlenecks in pharmaceutical R&D. The company has established enabling collaborations with Gilead in NASH and Bristol Myers Squibb in ALS. insitro is located in South San Francisco, CA and has been supported by top tech, biotech, and crossover investors since formation in 2018. For more information on insitro, please visit the company’s website at www.insitro.com.
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