Meet Biomni is a Stanford-based initiative that funds early-career researchers developing AI-powered biomedical co-scientist tools, aiming to accelerate drug discovery and personalized medicine through computational innovation. The programme exists to bridge the gap between AI/ML expertise and biomedical research, supporting independent thinkers who can build and validate novel platforms.

- Eligibility: Open to early-career researchers (pre-PhD, post-baccalaureate, or independent) with a focus on AI/ML in biomedicine; LMIC-track applicants encouraged. - Scoring rubric: Innovation (30%) – novelty of the AI/co-scientist approach; Feasibility (25%) – technical plan and validation; Impact (25%) – potential to transform biomedical research; Applicant fit (20%) – track record, independence, and collaborations. - Reviewer priorities: Demonstrated ability to build working platforms (e.g., IMPRINT, TOPOLOGIX), peer-reviewed or preprint evidence, and clear alignment with AI-powered biomedical co-scientist goals.

Past cohorts include independent researchers and recent graduates who have built AI-driven tools for drug repurposing, protein design, or clinical decision support. Named examples are not publicly listed on the Stanford page, but typical winners have 1-3 preprints, open-source code repositories, and endorsements from senior academics.

The platonic ideal applicant is an early-career researcher with a strong computational background, a proven track record of building AI/ML platforms for biomedical problems, and a clear vision for a co-scientist system that integrates multi-omics or pharmacological data. They have published preprints, maintain active GitHub repositories, and have secured endorsements from leading scientists in the field.