Cheminformatics and Machine Learning Intern

Department: AI

Location: NYC or SF Bay Area

Employment Type: Intern

Cheminformatics and Machine Learning Intern

Genesis Molecular AI is bringing together a world-class computational team to build out the industry's fastest and most accurate small molecule property predictions, by combining the power of machine learning and physics-based methods. We are seeking early career scientists skilled in developing and applying machine-learning, physics and cheminformatics methodologies to help drive forward our challenging drug discovery programs.

About the Role

This is an opportunity to operate as a full member of our ML and cheminformatics team and to make an impact on our internal ML and physics-based platform which drives our drug-discovery programs.

Your work will likely involve developing novel approaches to potency and ADME/PK property prediction, and prototyping integration with state-of-the-art tools for molecular modelling.

You Will

• Lead a novel research project from ideation to conclusion, focused on improving our internal tools for potency and ADME prediction.

• Prototype novel approaches from recent publications. Design and execute large-scale experiments to validate promising avenues, using internal and public benchmarks.

• Work closely with our computer-aided drug discovery scientists and medicinal chemists to develop, benchmark, and deploy improvements to our drug discovery platform as it is applied to our internal and partnered drug discovery programs.

You Are

• A graduate student with a proven track record of developing cheminformatics tools and/or physics methods in contexts relevant to drug discovery.

• Experienced Python programmer with proven ability to navigate and contribute to complex codebases.

• Proficient ML practitioner, familiar with common architectures (understanding their strengths and tradeoffs) and with proven expertise in troubleshooting real-world applications.

• A detail-oriented data scientist skilled in managing diverse data sources. Familiarity with RDKit, Openeye and other cheminformatics libraries is a plus.

• Passionate about making a direct impact on drug-discovery programs and interacting with a diverse team of ML practitioners, medicinal chemists and drug-discovery scientists.

What we offer

• The opportunity to work on challenging ML and cheminformatics problems that will directly impact our programs and inform the company’s mission to accelerate drug discovery.

• Dedicated mentorship from a senior researcher on our team who will partner with you, guide your project, and champion your growth.

• A world-class, mission-driven team of good-hearted people across software, machine learning, computational chemistry, medicinal chemistry, and biology.

About Genesis Molecular AI

Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. The company’s generative and predictive AI platform, GEMS (Genesis Exploration of Molecular Space), integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. Genesis has raised over $300 million from leading AI, tech and life science-focused investors, signed multiple AI-focused research collaborations with major pharma partners, and is deploying GEMS to advance an internal therapeutics pipeline for a variety of high-impact targets.

Genesis is headquartered in San Mateo, CA, with a fully integrated laboratory in San Diego. We are proud to be an inclusive workplace and an Equal Opportunity Employer.