AI@HHMI | HHMI

AI is reshaping the world at an extraordinary scale and pace, and its potential to transform innovation and discovery is boundless. Our vision is a future in which AI accelerates scientific discovery by speeding cycles of ideas, experiments, and data collection, rapidly unlocking a deeper understanding of life’s complexity and advances in human health.

To help realize AI’s immense promise in the life sciences, HHMI is investing $500 million over a 10-year period to support AI-driven projects and to embed AI systems throughout every stage of the scientific process in labs across HHMI. Critical to our vision is “AI-in-the-Loop,” an approach that places AI at the center of our scientific research to accelerate iterative cycles of experimental design and execution.

Join our AI experts in advancing critical, mission-driven work

All Open Positions

AI-in-the-Loop

We’re harnessing AI to help design experiments, build automated pipelines, collect high-quality data, and create generalizable learning models capable of inferring the underlying principles within that data.

Our AI experts and engineers — working in close collaboration with our biological scientists — play a crucial role in creating and curating new datasets and integrating AI into all phases of scientific discovery.

Current Projects

AI@HHMI projects have broad, dramatic implications for the acceleration of scientific discovery.

Luke Lavis, Senior Group Leader at Janelia, and David Baker, HHMI Investigator at the University of Washington, will use AI-driven de novo protein design to create specific protein binders for bright small-molecule fluorophores. These novel proteins will be further elaborated into fluorescent indicators and fluorophore ligases, yielding a suite of advanced tools to enable breakthrough imaging experiments.

Read more about the flurophore binder design project and the new class of imaging probes called NovoTags.

Erick Matsen and Jesse Bloom, HHMI Investigators at the Fred Hutchinson Cancer Center, will develop AI models that promise to transform our ability to forecast how protein sequences evolve over time, with broad implications for immunology, virology, and protein design.

Gerry Rubin, Senior Group Leader at Janelia, will lead a project to accelerate production of molecularly annotated connectomes in fruit fly and fish brains by physically expanding tissue samples to achieve nanoscale resolution with light microscopy and using AI to analyze these images.

Alison Tebo and Srini Turaga, Group Leaders at Janelia, will apply AI to the design of genetically encoded metabolic sensors. They will leverage both existing and newly generated mutational data from fluorescent biosensors to develop AI models that predict sequence-function relationships and guide the design of improved biosensors. This approach will deliver optimized sensors for key metabolic targets while establishing a generalizable framework that dramatically reduces biosensor development time.

Read more about the biosensors project and what they’ve developed so far.

Jakob Troidl, AI Scientist at Janelia, will lead a team of scientists and engineers in developing next-generation AI-driven microscopy image analysis tools. This includes the curation and assembly of foundational, multi-modal microscopy datasets, alongside the design of AI models capable of generalizing across a broad spectrum of image analysis tasks.

Eric Gouaux and Mike Rosen, HHMI Investigators at Oregon Health & Science University and UT Southwestern, respectively, plan to combine AI with novel experimental strategies to interpret cryo-electron tomography (cryo-ET) images of elusive protein complexes within synapses and cellular nuclei.

Rhiju Das, HHMI Investigator at Stanford University, will lead a project that integrates AI with gigascale biochemical datasets and internet-scale crowdsourcing to advance RNA 3Dstructure prediction.

Michael Reiser, Senior Group Leader at Janelia, and Mark J. Schnitzer, HHMI Investigator at Stanford University, will develop autonomous robotic systems for dextrous handling and experimenting with individual Drosophila. When paired with AI-in-the-loop experiment control, the platform will remove the manual bottleneck in fly preparation and enable previously infeasible large-scale screening across genetics, behavior, and neural function

Misha Ahrens, Senior Group Leader at Janelia, will lead a team of researchers using AI to build biologically grounded models of larval zebrafish that link cellular activity in the brain and body with neural connectomes, behavior, and learning.

Janelia Research Campus — at the forefront of AI-driven research

Janelia has been at the forefront of AI-driven biological research for more than 15 years. Its uniquely nimble structure and collaborative culture make it ideally suited for this ambitious work, whether building machine-learning systems to tackle major challenges within the life sciences, or establishing productive, ongoing partnerships with AI industry leaders.

These collaborations, which include scientists within and beyond Janelia, have yielded a range of significant breakthroughs, including the first detailed map of an adult fly brain. These projects reflect Janelia’s incredible capacity to generate large, high-quality datasets that benefit the entire scientific community.

Join our ai@hhmi Team

We’re hiring a dedicated team of AI scientists, AI engineers, robotics engineers, and data scientists

Our AI scientists self-assemble into small teams and work closely with scientists from across the broader HHMI community — HHMI Investigators, Freeman Hrabowski Scholars, Janelia-based scientists, and more — to help design and execute a wide range of ambitious, AI-based biomedical research projects.

Projects are reviewed regularly by HHMI and Janelia leadership, and the most promising ideas are implemented using Janelia’s unique Project Team system, which enables the execution of projects larger than any single lab can perform on its own. This flexible, collaborative structure allows us to quickly and efficiently pursue the best ideas as they arise, and to direct resources to new projects when older ones are complete.

Learn more about working at Janelia.