About Us:
Grafton Biosciences is a stealth-mode, San Francisco-based biotech startup focused on solving disease through groundbreaking innovations in early detection and therapeutics. We are combining breakthroughs in synthetic biology, machine learning, and manufacturing to fundamentally extend healthy human lifespans. We’re looking for passionate team members who want to shape the future.
Role: Generative AI Scientist, Computational Chemistry & Drug Discovery
We are seeking a highly specialized scientist at the intersection of machine learning, chemistry, and biology. Your primary focus will be on adapting and creating novel generative AI models to revolutionize our drug discovery process, with a specific emphasis on molecular docking and binding prediction. The ideal candidate is not just a data scientist, but a computational biology scientist who has hands-on experience modifying the core engines of docking and folding software. You will work in close collaboration with our computational chemistry and biology teams to design novel therapeutics.
Key Responsibilities:
Qualifications:
To address the specific needs of this role, candidates must demonstrate experience in the following core areas. Applications without this experience will not be considered .
Essential Qualifications:
Preferred Qualifications:
What We Offer:
Screening Questions
If you are a particularly good fit for this role , please email careers@graftonbio.com with responses to the following questions. The email subject should be: GenAI Scientist - [Your Last Name].
(1) Please describe one project where you personally applied machine-learning methods to a complex biological or chemical dataset (e.g., structural biology, proteomics, HTS, cheminformatics). Be sure to cover:
We’re looking for evidence that you understand the science driving the data—not just the algorithms.
(2) Please outline your hands-on experience modifying, customizing, or creating generative AI-based molecular docking software (e.g., DiffDock, NeuralPlexer, GNINA). In bullet form, address the following:
This role requires deeper engagement than simply running pre-built docking tools—please highlight modifications you personally implemented.
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