An experienced chemist or chemist-in-training is sought. Expertise in chemical synthesis and purification is required. Duties will include acquiring accurate and precise data to build data sets at the intersection of chemistry and biology. Machine learning integrated with chemistry/biology at scale lies at the core of insitro’s approach to rethinking drug discovery and development. As our Associate Scientist you will be a key member of the High-Throughput Chemistry team working on the synthesis of DNA-Encoded chemical Libraries (DELs) and subsequently screening these DELs using the company’s proprietary nDexer platform for drug discovery. You will be a member of cross-functional teams, comprising machine learning engineers, life scientists, automation engineers and data scientists. You will demonstrate world-class research skills and experience in developing and using cutting-edge molecular biology methods. You will hone your interpersonal skills, and build a strong collaborative work ethic, as well as the ability to adapt to changing needs, and the capacity to multitask to meet key goals. Exceptional attention to detail and communication skills are essential to success in this position.
Specifically, you will:
You will be joining the founding team of a biotech startup that has long-term stability due to significant funding, but yet is very much in formation. Much can change in this early and exciting phase, providing many opportunities for significant impact. You will work closely with an exceptionally talented team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!
Nice to Have
Benefits at insitro
insitro is a data-driven drug discovery and development company using machine learning and high-throughput biology to transform the way that drugs are discovered and delivered to patients. The company is applying state-of-the-art technologies from bioengineering to create massive data sets that enable the power of modern machine learning methods to be brought to bear on key bottlenecks in pharmaceutical R&D. The resulting predictive models are used to accelerate target selection, to design and develop effective therapeutics, and to inform clinical strategy. insitro was launched in 2018 with a Series A of $100M funded by top investors including a16z, Arch Venture Partners, Foresite Capital, GV, and Third Rock Ventures. In 2019 the company announced a collaboration with Gilead Sciences in the area of NASH, a collaboration with BMS in the area of ALS, and in mid 2020, announced a Series B financing of $143M including current investors and new investors Canada Pension Plan Investment Board (CPP Investments), T. Rowe Price, BlackRock, Casdin Capital and other leading investors. The company is located in South San Francisco, CA. For more information about insitro, please visit the company’s website at www.insitro.com
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