Computational Biologist

About the role

Blank Bio is an applied AI research lab dedicated to enhancing clinical trial success rates through the development of RNA foundation models that capture disease progression and patient responses to treatments. Our team includes experts from leading institutions and companies, working towards making informed decisions in pharmaceuticals by understanding the unique biology of each patient's tumor.

Responsibilities

• Apply Blank Bio’s foundation models and embeddings to real-world clinical datasets to identify predictive and prognostic biomarker case studies in oncology.
• Analyze literature, clinical trial readouts, regulatory submissions, and biomarker strategies to inform modeling priorities and business development strategy.
• Curate biomarker-relevant evaluation tasks and datasets that reflect clinically meaningful biology, feeding directly into the research team’s benchmark development.

Qualifications

• Must-have: PhD (or equivalent experience) in computational biology, RNA biology, cancer biology, genomics, bioinformatics, or a related quantitative biomedical field.
• Strong ability to connect model outputs, statistical results, and biological context into clear scientific conclusions.
• Excellent written communication skills, capable of writing for both technical and non-technical audiences.
• Experience with large-scale omics analyses across public or clinical datasets, such as TCGA, GTEx, ICGC, GEO, dbGaP, or similar resources.

Nice-to-haves

• Familiarity with clinical trial design, including endpoints, patient stratification, all-comer studies, and biomarker-guided trials.
• Experience with ML model evaluation, embeddings, representation learning, or benchmark design in biology.
• Prior collaboration with clinical researchers, diagnostic developers, or biomarker discovery teams.
• Previous work in an early-stage, fast-paced environment.

Compensation & Benefits

• Competitive salary and meaningful early-stage equity.
• Comprehensive health, dental, and vision coverage.
• Generous vacation and parental leave policies.