Machine learning integrated with biology at scale lies at the core of insitro’s approach to rethinking drug discovery and development. As a high-throughput biology fellow you will help us to test and validate innovative technology in genetic perturbation, functional genomics and imaging. You will work closely with our Data Engineering, Process Engineering, Machine Learning, Translational Science, Molecular Design and Disease Modeling Teams team to productionize validated technologies and explore translational applications. You will bring cutting-edge expertise to build sophisticated molecular assays using first principles and enhance our abilities to collect more comprehensive and precise phenotypic measurements across a multitude of cell-types, assay conditions, and therapeutic areas. You will have demonstrated your ability to perform independent troubleshooting on complex workflows, to work in a highly cross-disciplinary, fast-moving and fluid environment, and to consistently deliver high quality data that has driven platform projects forward. You possess a strong collaborative work ethic, ability to adapt to changing needs, and the capacity to multitask to meet key goals. Strong communication and presentation skills are essential to success in this position. You will be a temporary employee that spends 6 months to 1 year working on a specific focused project and have an opportunity to learn about industry and start up life. 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!
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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 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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