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An established industry player in biotechnology is seeking a talented individual contributor to join their innovative team. This role involves leveraging advanced computational chemistry techniques to drive drug discovery efforts. You'll be at the forefront of integrating AI and biological automation, contributing to the design of drug-like molecules. The position offers a unique opportunity to work on cutting-edge research, collaborate with a dynamic team, and enhance your skills in computational life sciences. If you're passionate about making a difference in the field of drug development, this is the perfect opportunity for you.
1910 Genetics is the only company that has built a synergistic, dual-purpose small and large molecule platform that integrates artificial intelligence (AI), computation, and biological automation to design drug-like molecules better, faster, and cheaper than traditional approaches. Based in the Seaport District of Boston, 1910 Genetics is a Series A stage biotechnology startup that was founded in 2018 and is backed by prestigious investors, including M12-Microsoft’s Venture Fund, Sam Altman – the CEO of OpenAI (makers of ChatGPT), Playground Global, Y Combinator, New Ventures Funds (Scientia Ventures), and many others.
At 1910 Genetics, we first established an understanding of the molecular basis of disease to the granularity at which the world understands sickle cell anemia. This understanding centers biology as our North Star and drives our integration of artificial intelligence (AI), computation, and biological automation to accelerate the design of small molecule and protein therapeutics.
Recent advances in computational technologies have placed historically “undruggable” targets within therapeutic reach. But at 1910 Genetics, we often say “Biology is King,” meaning that computational technologies are only impactful in drug discovery when driven by experimental biology. Our platforms’ scale and breadth empower us to be therapeutic area-agnostic with programs ranging from neuroscience and immunology to infectious disease and oncology, to name a few.
Roll up their sleeves as an Individual Contributor (IC) by keeping up with relevant scientific literature, simulating biochemical processes for use as training data in AI/ML models, and contributing to our active drug design campaigns by providing computational guidance during the design phase.