Job description

About Arc Institute Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco. Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone. Our two Institute Initiatives reflect this model in action: Virtual Cell Initiative : Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets, accelerating the path from biological insight to clinical trials. Alzheimer's Disease Initiative : Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes. More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding. About the position The Hsu Lab is looking for postdoctoral researchers, who are curious, creative and motivated to advance the state-of-the-art in generative AI applied to biology, including Arc’s frontier biological foundation models (Evo, Evo 2, State, Stack, Bioreason, and beyond). The successful candidate is passionate about developing ML models for biological understanding and design, leveraging frontier approaches such as novel ML architectures, post-training, agentic reasoning, and more. Current areas of interest of the lab include building predictive models of life (e.g. by integrating Evo and State), AI agents and systems, genome mining, and invention of new therapeutics through AI-guided approaches. Postdocs in the lab are encouraged to lead ambitious, independent projects, resulting in high-impact publications. You will have the opportunity to collaborate widely across Arc, Stanford, and the broader Bay Area ecosystem, with access to strong platforms in our lab and our institutions for genomics, single-cell technologies, synthetic biology, high-performance computing clusters, and experimental model systems. About you Extremely Curious & Self-Motivated: You push the boundaries of machine learning, biotechnology, and/or biomedical research. High-Velocity Researcher: You thrive in a fast-paced environment and have a bias for action, conducting rigorous and impactful research at scale. Intellectually Independent: You are a "first-principles" thinker, able to design new research directions and projects. Technical Polyglot: You are comfortable (or eager to become so) at the intersection of ML and computational biology, and eager to collaborate with wet-lab scientists. Puzzle Solver: You are excited by solving puzzles that have a translational impact and/or creating new therapeutic approaches. In this position you will Conduct high-impact research: Design, execute, and analyze computational experiments; take end-to-end ownership of a research project within the lab’s scientific focus, with guidance from the PI and increasing independence as you develop expertise. Develop as a future scientific leader: Publish first-author papers in high-impact journals, present at national and international conferences, and build a network of collaborators across Arc, Stanford, and beyond. Foster scientific excellence: Mentor and train research associates, technicians, and students; engage in Arc-wide activities (seminars, symposia); contribute to a collaborative research environment; maintain rigorous coding standards and documentation; and contribute to lab operations including software development and maintaining shared infrastructure. Requirements Ph.D. in Computer Science, Bioinformatics, Computational Biology, Genetics/Genomics Expertise with Python, bash, and standard deep learning frameworks such as PyTorch. Excellent written and verbal communication skills. Demonstrated ability to work in a fast-paced environment and be both an independent thinker and a highly collaborative team player. Track record of creative, high-impact research as demonstrated by publications, patents, developed tools, software etc. The minimum base salary for this position is $80,000. Base salary for this role is determined by how many months of relevant postdoctoral experience a successful candidate has. Base salary for this role is not negotiable.

Requirements

Must-haves

Extremely Curious & Self-Motivated: You push the boundaries of machine learning, biotechnology, and/or biomedical research.
High-Velocity Researcher: You thrive in a fast-paced environment and have a bias for action, conducting rigorous and impactful research at scale.
Intellectually Independent: You are a "first-principles" thinker, able to design new research directions and projects.
Technical Polyglot: You are comfortable (or eager to become so) at the intersection of ML and computational biology, and eager to collaborate with wet-lab scientists.
Puzzle Solver: You are excited by solving puzzles that have a translational impact and/or creating new therapeutic approaches.
In this position you will
Develop as a future scientific leader: Publish first-author papers in high-impact journals, present at national and international conferences, and build a network of collaborators across Arc, Stanford, and beyond.
Ph.D. in Computer Science, Bioinformatics, Computational Biology, Genetics/Genomics
Expertise with Python, bash, and standard deep learning frameworks such as PyTorch.
Excellent written and verbal communication skills.
Demonstrated ability to work in a fast-paced environment and be both an independent thinker and a highly collaborative team player.
Track record of creative, high-impact research as demonstrated by publications, patents, developed tools, software etc.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningpython

Platform: greenhouse
Effort: quick