Senior Scientist I, Computational Biology

Cambridge, MAOnsiteFull TimeSenior$130,000–$170,000 /yrPosted 9 days agoVisa sponsorship available

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Required skills

quantitative discipline
biotech
pharma
academia
preclinical datasets
data-driven approaches
biological research
methodological assumptions
limitations
biological implications

Nice to have

CAR biology
immunology
cell therapy
RNA therapeutics
integrating heterogeneous datasets
meta-analysis

Role summary

Sail Biomedicines is seeking a Senior Scientist I, Computational Biology to drive the future of programmable eRNA TM therapeutics and In Vivo CAR-T therapies. This role involves applying data-driven approaches to analyze preclinical datasets and champion platform efforts. Responsibilities include leading data analysis, developing and benchmarking computational methods, integrating and interpreting data, partnering with experimental scientists, and building reproducible analysis workflows. The ideal candidate will have a Ph.D. in a related quantitative discipline, 3+ years of experience, strong programming skills in Python and/or R, and expertise in statistical modeling and multi-omics analysis. Preferred experience includes CAR biology, immunology, cell therapy, or RNA therapeutics.

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.

Deep expertise in at least one relevant area, such 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, with demonstrated 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.

Demonstrated ability to collaborate effectively with experimental scientists, take ownership of scientific questions, be a proactive force driving improvement, and being comfortable developing to contribute beyond your core area of expertise.

Preferred:

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 to cloud-based or collaborative data environments

Track record of impactful scientific contributions (publications or program support)

Computational protein design and / or structural biology experience a plus

About Sail Biomedicines

Sail Biomedicines is building a new class of fully programmable medicines by integrating circular RNA (eRNA™), targeted nanoparticle delivery, and advanced computational approaches. Our platform enables the systematic design and optimization of therapies, unlocking new possibilities across immunology and beyond.

Salary Range: $130,000 - $170,000

Sail Biomedicines is an Equal Opportunity Employer. Sail does not discriminate based on race, religion, color, sex, gender identity, sexual orientation, age, national origin, veteran status, or any other status protected under federal, state, or local law.

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