Own a significant research initiative addressing a key challenge in molecular AI, from conception through completion.
Advance techniques in areas like diffusion, language models, reinforcement learning, or cross-modal approaches.
Execute experiments at scale to test and validate your most promising ideas.
Share results with colleagues, potentially contributing to publications in premier journals.
What they're looking for
PhD student in Computer Science, Machine Learning, or closely related discipline.
Solid expertise in machine and deep learning with an analytical, foundational approach to problems.
Interest in tackling complex scientific questions and enthusiasm for the AI-biochemistry intersection.
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
About Genesis Molecular AI
Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. Our 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 is backed by premier AI and life science investors, including a16z, NVIDIA, Rock Springs Capital, Menlo Ventures, T. Rowe Price, Fidelity, and Radical Ventures. Genesis has also signed category-leading AI-pharma deals, the most recent of which was a significant expansion with Incyte (see coverage in Forbes and GEN) with a total potential deal value of several billion dollars.
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.
From Genesis Molecular AI's public posting, laid out for reading by newgrad.ai with the wording unchanged. Check the original before you apply.
