Basis is a nonprofit applied research organization with two mutually reinforcing goals.

Basis is building AI technology to solve hard computational problems, and using that technology to help address socially-important challenge problems. To accomplish these two mutually reinforcing goals, we are actively soliciting researchers in our core technical areas and domain experts from academia, government, the social sector, and industry to join us in a new kind of collaborative endeavor.

Collaborators

If you or your organization are interested in working together on our current challenge problems or proposing new ones, or on research and open source software development, we want to hear from you! Please reach out to us at contact@basis.ai.

Fellowships

Basis sponsors postdoctoral fellowships for early-career scientists who share our mission to understand and build intelligence. Fellows have autonomy to direct their own research, and work with Basis scientists and our academic collaborators.

Please see more information and application here.

Careers

We are looking for people who are excited to contribute to Basis’ technical mission, want to work creatively on projects that matter with impact that goes beyond publications, and enjoy collaborating with a broad community of people while shipping high quality open source software.

Our organizational structure makes for a distinct form of career development where employees are able to see their autonomy and responsibilities grow with their projects.

Open Roles

NY | Boston — Probabilistic machine learning and causal inference.


NY | Boston — Programming language / compiler design and implementation.


NY | Boston — Translate research ideas into correct, robust, and scalable high-quality code.


NY | Boston — Communicate our research to funders, the scientific community, and the public.


NY — Postdoctoral Fellowship on perception and model learning.


Boston — Postdoctoral Fellowship on LLM-based reasoning systems.


Farmington | Boston | NY — Postdoctoral Fellowship on whole-cell model-driven gene function discovery.