Cheminformatics and Machine Learning Intern

• Lead a novel research project from ideation to conclusion, focused on improving internal tools for potency and ADME prediction.
• Prototype novel approaches from recent publications and design/execute large-scale experiments to validate promising avenues.
• Work closely with computer-aided drug discovery scientists and medicinal chemists to develop, benchmark, and deploy improvements to the drug discovery platform.

This role creates positive change by directly impacting drug-discovery programs and accelerating the company's mission to develop new therapeutics for high-impact targets, potentially leading to breakthrough treatments for various diseases.

• Graduate student with proven track record of developing cheminformatics tools and/or physics methods relevant to drug discovery.
• Experienced Python programmer with ability to navigate and contribute to complex codebases.
• Proficient ML practitioner familiar with common architectures and troubleshooting real-world applications.
• Detail-oriented data scientist skilled in managing diverse data sources, with familiarity with RDKit, Openeye and other cheminformatics libraries as a plus.

• Opportunity to work on challenging ML and cheminformatics problems that directly impact programs and inform the company's mission.
• Dedicated mentorship from a senior researcher who will partner, guide projects, and champion growth.
• World-class, mission-driven team of good-hearted people across software, machine learning, computational chemistry, medicinal chemistry, and biology.

Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development through its generative and predictive AI platform GEMS, which integrates AI and physics into industry-leading models to generate and optimize drug molecules.