Senior Scientist I, Computational Biology
About The Position
Join Sail Biomedicines’ Computational Biology team to help advance programmable eRNA therapeutics and in vivo CAR-T therapies. The Senior Scientist I works at the interface of platform development and therapeutic programs, applying data-driven approaches to platform initiatives and analyzing preclinical datasets to support treatments for autoimmune diseases and beyond. The role supports in vivo CAR-T immunology programs and platform development, with opportunities to contribute to capabilities in molecular and systems modeling, computational protein design, and AI-based therapeutic engineering. The ideal candidate has a strong computational biology foundation and can independently develop, implement, and critically evaluate methods for biological research, reasoning from raw measurements through methodological limitations and biological interpretation. Sail Biomedicines is building programmable medicines by integrating circular RNA (eRNA™), targeted nanoparticle delivery, and computational approaches to design and optimize therapies.
Requirements
- Ph.D. in Computational Biology, Bioinformatics, Systems Biology, Biophysics, or a related quantitative discipline.
- At least 3 years of hands-on computational biology research in biotech, pharma, or academia.
- 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.
- Deep expertise in at least one relevant area, such as transcriptomics, multi-omics analysis, or quantitative analysis of preclinical studies, spanning data generation, quality control, methodological choices, and biological interpretation.
- Strong grounding in statistical modeling, including the ability to address confounding, batch effects, biological versus technical variation, and experimental-design limitations, and to assess uncertainty and sensitivity to analytical choices.
- Strong programming skills in Python and/or R, with experience independently developing and maintaining reproducible, well-documented scientific analysis code and workflows.
- Ability to collaborate effectively with experimental scientists, take ownership of scientific questions, proactively drive improvement, and contribute beyond the core area of expertise.
Nice To Haves
- Experience in CAR biology, immunology, cell therapy, or RNA therapeutics.
- Experience integrating heterogeneous datasets across studies or conducting meta-analysis.
- Experience with workflow orchestration tools for cloud-based or collaborative data environments.
- Track record of impactful scientific contributions, such as publications or program support.
- Experience in computational protein design and/or structural biology.
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 using internal and external resources to contextualize findings, evaluate consistency, and strengthen understanding of 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 Git version control, consistent data annotation, and metadata practices.
- Communicate findings, uncertainty, and implications to collaborators through visualizations, presentations, and written summaries.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
