Member of Technical Staff: Computational Biology

Radical Numerics • San Francisco, CA

3d

About The Position

Radical Numerics is an AI research lab focused on biological intelligence and developing both the ability to design biological systems and the responsibility to defend against misuse. The lab has developed biological AI models and research projects, including Evo, Evo 2, and Omnii-1.

The Computational Biology role applies deep biological expertise to the data, tasks, and analyses behind the lab’s models. The successful candidate will translate questions in genomics, gene regulation, protein biology, systems biology, or another specialty into well-defined computational work and interpret results using sound scientific judgment. The role may be shaped around a specialty such as data curation, bioinformatics pipelines, or model evaluation. The candidate will work with model researchers and experimental collaborators to create datasets and analyses that support scientific work.

Radical Numerics is committed to equal employment opportunity and does not discriminate on the basis of protected characteristics. The company participates in E-Verify and provides Form I-9 information to the federal government to confirm U.S. work authorization.

Requirements

• An exceptional research record in computational biology, bioinformatics, genomics, or another relevant area of biology, demonstrated through a PhD or equivalent research or industry experience.
• Deep expertise in at least one biological domain, with strong scientific judgment and careful attention to data quality and experimental details.
• Strong Python or R programming skills and experience building reliable, reproducible scientific analyses or software.
• Ability to work across biology, machine learning, and engineering, and communicate assumptions, results, and limitations clearly.
• Experience working with agentic coding tools.

Nice To Haves

• Experience with large-scale biological data curation, data mixing, or bioinformatics infrastructure.
• Experience with biological foundation models or research contributions, datasets, methods, or software used by other scientists.

Responsibilities

• Curate and integrate large biological datasets with clear provenance, quality control, and documented assumptions.
• Build reproducible bioinformatics and analysis pipelines for relevant data, such as sequencing, functional genomics, single-cell, perturbational screening, or protein data.
• Help design data mixtures and sampling strategies for model training.
• Investigate how dataset composition, assay effects, duplication, and biological coverage affect downstream results.
• Define biologically meaningful tasks, endpoints, and baselines with modeling and evaluation teams.
• Investigate model predictions and failure modes in the context of available biological evidence.
• Work with wet-lab collaborators to formulate testable hypotheses, prioritize validation experiments, and generate new training datasets.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed