ML Research Intern – PhD (Summer 2027)

About the Team

Join a world-class team at the forefront of AI and biochemistry.

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.

About the Role

This is an opportunity to operate as a full member of our research team and to drive forward our ML research agenda for generative modeling of molecular systems. You will be paired with a mentor to work on a high-impact research project at the frontier of generative AI. Your work will likely involve making advancements to novel foundation models, with potential projects in areas like diffusion models, large language models (LLMs), reinforcement learning (RL), and multi-modal learning. We’re looking for exceptional PhD candidates passionate about conducting novel research that contributes directly to our mission of discovering new medicines.

You Will:

• Lead a novel research project from ideation to conclusion, focused on a critical challenge in generative or predictive AI for molecular systems.

• Push the research frontier by engaging with the latest literature on foundation models, developing new methods in areas like diffusion or RL, and rigorously testing your hypotheses at scale.

• Design and run experiments at scale to validate most promising approaches and hypotheses.

• Present your work to the team and contribute your insights to our broader research agenda. Strong internship projects may lead to publications in top-tier venues.

You Are:

• Currently enrolled in a PhD program in Computer Science, Machine Learning, or related fields.

• A creative researcher with a strong background in machine learning, deep learning, and/or related areas.

• A first-principles thinker who is passionate about tackling open-ended scientific problems.

• Curious about the intersection of AI and biochemistry and excited to learn about the drug discovery process.

What we offer:

• A high-impact research project, not a toy problem. Your work is chosen to have a direct line of sight to advancing our core scientific platform.

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

• Deep immersion in a world-class team. You'll join our paper discussions, research talks, and social events, becoming a true member of the Genesis AI team. The team reads and discusses 1-2 ML or chemistry papers every week to stay on top of the field and inspire new ideas.

Past intern projects include:

• Developing a post-training protocol to improve LLM reasoning for drug discovery tasks

• Designing a more efficient co-folding model architecture

• Building a vector embedding method to tractably search billions-scale molecule libraries

• Optimizing reinforcement learning algorithms to improve state-of-the-art diffusion models

• Inventing novel inference-time steering methods to enhance co-folding model performance in the hands of chemists