2027 Future Talent Program - Translational Genome Analytics - Co-op
About The Position
The Research & Development Division Data, AI & Genome Sciences (D&GS) 2027 Future Talent Program is offering two computational co-op positions for a six-month term. The positions provide students hands-on experience applying computational methods to drug-discovery questions, developing their skills, and helping both the student and team evaluate longer-term fit. The program seeks students with strong computational and quantitative skills. The Computational Oncology co-op analyzes and integrates large transcriptomic datasets to understand tumor biology and support target and biomarker discovery. Projects may involve bulk and single-cell RNA-seq quality control, cell-type annotation, characterization of tumor and tumor-microenvironment cell states, linking molecular profiles with drug and therapy response, characterizing transcriptional responses to therapeutic perturbations, and creating reproducible analyses and visualizations for project teams. The Computational Immunology co-op applies computational methods to immune-profiling datasets to understand disease biology and immune responses and support target evaluation. Projects may involve analyzing immune-focused sequencing data to characterize immune cell states across disease and treatment, analyzing and implementing methods to study interactions among disease-relevant biological networks, and mining internal and external molecular databases for therapeutic discovery, disease stratification, and biomarker identification. The positions are full-time for six months. Locations are Cambridge, Massachusetts; Boston, Massachusetts; or South San Francisco, California. Remote work may be considered, and the listed flexible work arrangement is hybrid. The role is designated Intern/Co-op (Fixed Term). No relocation, visa sponsorship, or travel is offered or required.
Requirements
- Currently enrolled in at least a bachelor's degree program in biological sciences, computational biology, bioinformatics, or a related quantitative field.
- Available to work full-time for six months.
Nice To Haves
- Students in graduate programs (MS or PhD) are highly encouraged to apply.
- Excellent academic achievement and analytical ability.
- Strong communication and interpersonal skills, and the ability to work well in a collaborative team.
- Demonstrated interest or experience in molecular biology, immunology, oncology, cancer biology, neuroscience, or bioinformatics.
- Programming experience in R and/or Python.
- Experience analyzing bulk or single-cell sequencing datasets, such as RNA-seq or scRNA-seq, and familiarity with standard statistical and visualization methods.
- Comfort working with large datasets and cloud or high-performance computing environments.
Responsibilities
- Analyze and integrate large transcriptomic datasets to understand tumor biology and support target and biomarker discovery.
- Perform quality control, cell-type annotation, and characterization of tumor and tumor-microenvironment cell states using bulk and single-cell RNA-seq data.
- Relate molecular profiles to drug and therapy response using large-scale screening and sequencing datasets to help prioritize and evaluate candidate targets.
- Characterize transcriptional responses to therapeutic perturbations to inform mechanisms of action.
- Build clear, reproducible analyses and visualizations that communicate findings to project teams.
- Analyze immune-focused sequencing data to characterize immune cell states and changes across disease and treatment.
- Analyze, implement, and visualize methods for studying interactions among disease-relevant biological networks.
- Mine internal and external molecular databases to support therapeutic discovery, disease stratification, and biomarker identification.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
