Radical Numerics is building biological AI to understand, predict, and design biology while strengthening defenses against biological threats. Backed by Emergence Capital.
About the role
As a Member of Technical Staff focused on statistical genetics, you will help us turn genetic association data into a rigorous substrate for biological foundation models. You will work with diverse data streams from GWAS, QTLs, variant annotation, biobank-scale phenotypes, and functional genomics to ask a central question: do our models understand the structure of genetic variation and its relationship to molecular and organismal traits? Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- PhD in statistical genetics, human genetics, computational biology, biostatistics, or a related field, OR substantial industry experience working with population-scale genetic data
- Deep working knowledge of concepts and methods in statistical genetics: GWAS, LD, ancestry/population structure, heritability, fine-mapping, QTL mapping, rare variant analysis, polygenic risk, and variant annotation
- Experience with large genetic resources such as UK Biobank, All of Us, TOPMed, gnomAD, GTEx, FinnGen, ENCODE, or similar datasets
- Strong Python or R programming skills and experience building reliable, reproducible scientific analyses or software. Experience working with agentic coding tools
- Clear communicator who can bridge scientific context with engineering teams and partner organizations
- Curiosity and resilience when tackling open-ended scientific challenges
More about this role
Radical Numerics is an AI research lab building general biological intelligence. Our mission is to master the code of life, and our purpose is to reduce human suffering.
Our team created Evo, and started the field of generative genomics . Our work was featured on the cover of Science , and presented by our CEO on the main stage of TED2025 . Evo was used to create the first AI-generated CRISPR-Cas9, and the first AI whole genome from scratch. Evo 2 , featured in Nature, is the largest fully open source AI project across any domain.
In October, we introduced Omnii-1, the world's most advanced multimodal genome language model, and a leap toward general biological intelligence. It unifies 28 biological modalities, spanning DNA, RNA, proteins, epigenomics, and more, in a single model trained on trillions of tokens of biological data In a world first , Omnii-1 designed the first AI-generated bacteriophages to be administered to a human patient with an antibiotic-resistant infection under compassionate use. We released this news alongside seven other project areas , showing the model’s breadth of applications.
The same generative breakthroughs that enable life-saving cures also lowers...
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