Genesis pairs frontier AI with world-class drug hunters to discover small molecule medicines. Built on Pearl and GEMS. Partnered with Gilead and Incyte. Backed by a16z.
About the role
This unique role is for a scientist who is passionate about being a catalyst for applying cutting-edge AI to solve real-world drug discovery challenges. You will be the critical bridge between our long-term research and our experimental drug discovery programs. Your mission is to build, evaluate, monitor, and improve our state-of-the-art models directly into active drug programs, leading the charge on model validation, deployment, and analysis to guide the discovery of new medicines. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- A seasoned computational scientist with a proven track record of machine learning based methods to impact small molecule drug discovery projects
- A cheminformatics expert , fluent in the language of molecular data with hands-on mastery of tools like RDKit or OpenEye
- A scientist who speaks the language of experimental drug discovery, with a strong familiarity with common assay types (biochemical/binding/cell-based assays, in vivo studies, etc.) and CADD workflows (docking, virtual screening, ADME prediction, etc.)
- A rigorous data scientist, with experience inmodeling and analysis of small molecule datasets and passion for statistical validation, uncertainty quantification, and deriving clear insights from complex, noisy data
- A hands-on applied scientist and software engineer with strong coding skills in Python and a deep practical knowledge of the applied ML toolkit (e.g., scikit-learn, PyTorch)
- An exceptional communicator and collaborator , able to act as the bridge between machine learning researchers and experimental scientists
More about this role
At Genesis Molecular AI, we’re a tight-knit team of proven deep learning researchers, software engineers, and drug discovery pioneers. Our shared mission is nothing short of revolutionary: to forge the next generation of AI foundation models that will unlock groundbreaking therapies for patients with severe diseases.
We don’t just apply machine learning to biology; we are conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field. You will work side-by-side with top multidisciplinary researchers to design and build generative foundation models at scale, having access to ample compute and large-scale simulations.
This unique role is for a scientist who is passionate about being a catalyst for applying cutting-edge AI to solve real-world drug discovery challenges. You will be the critical bridge between our long-term research and our experimental drug discovery programs. Your mission is to build, evaluate, monitor, and improve our state-of-the-art models directly into active drug programs, leading the charge on model validation, deployment, and analysis to guide the discovery of new...
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