The Position

Join our team and drive the future of programmable eRNATM therapeutics and In Vivo CAR-T therapies- where artificial intelligence, targeted delivery systems and next-generation immunotherapy converge to redefine what’s possible for patients. As a key member of the Sail Biomedicines Computational Biology team, the Senior Scientist I will operate at the interface of platform and program, applying data-driven approaches to champion broad platform efforts and hands-on analysis of preclinical datasets to transform the treatment landscape for autoimmune diseases, and beyond.

The ideal candidate brings a strong foundation in computational biology and a record of independently developing, implementing, and critically evaluating computational methods for biological research. They should be comfortable reasoning through methodological assumptions, limitations, and biological implications of an analysis, from raw measurements through interpretation.

The role will directly support In Vivo CAR-T immunology programs and platform development, with opportunities to contribute to building capabilities spanning molecular and systems modeling, computational protein design, and AI-based therapeutic engineering.

Responsibilities

• Lead analysis of preclinical research datasets, including immunophenotyping, functional assays, and multi-omics data to support therapeutic development
• Develop, adapt, and benchmark computational and statistical methods to address biological questions where standard workflows are insufficient
• Integrate and interpret data across studies leveraging internal and external resources to contextualize findings, evaluate consistency, and strengthen understanding of our therapeutics
• Partner with experimental scientists to shape experimental design, identify limitations, interpret results, and prioritize follow-up studies.
• Build and maintain reproducible analysis workflows, with clear documentation and version control (Git) with consistent data annotation and metadata practices.
• Communicate findings, uncertainty, and implications with collaborators through effective visualizations, presentations, and written summaries

Qualifications

Required:

• Ph.D. in Computational Biology, Bioinformatics, Systems Biology, Biophysics, or a related quantitative discipline.
• 3+ years of hands-on computational biology research in biotech, pharma, or academia.
• A record of independently leading substantial computational biology projects, including developing, adapting, and benchmarking analytical methods. Evidence may include methods development, reusable scientific software, publications, or documented contributions to therapeutic research.