Staff Machine Learning and Bioinformatics Scientist (Multi-Cancer Early Detection)

Role overview Develop machine learning and statistical methods to detect cancer signals in multimodal genomic data. The role connects research with practical implementation: models move from prototypes to scalable systems and clinical validation, in close partnership with molecular biology and clinical specialists. The position is remote within the United States and centers on cancer detection research.

Responsibilities - Lead development of new statistical and machine learning methods for cancer signal detection across genomic data types. - Build interpretable, well-calibrated models, with careful uncertainty estimates and reproducible analysis. - Prototype, evaluate, and productionize models using scalable computing infrastructure. - Own technical deliverables and contribute to research planning. - Design experiments and validation studies with molecular biologists and clinical experts. - Review code and model designs, communicate findings to varied audiences, and mentor junior scientists.

Requirements - PhD in computer science, mathematics, bioinformatics, or a related quantitative field, with 6–12 years of postdoctoral experience. - Demonstrated work developing statistical or machine learning methods for complex biological data. - Technical leadership and a record of innovation in challenging method-development work. - Expertise in deep learning and multimodal foundation models. - Strong Python skills and familiarity with its scientific computing ecosystem. - Scientific rigor, clear communication, and a collaborative approach to research and learning.

Nice to have - Experience with DNA methylation, epigenomics, cell-free DNA, or liquid biopsy data. - Background in cancer genomics or diagnostics, including multimodal foundation models applied to biological data.

Benefits and work setup - Remote work within the United States. - Benefits include medical, dental, vision, life, and disability coverage for eligible employees and dependents, along with family testing, fertility care, parental leave, retirement savings, commuter support, and referral benefits.