2027 Future Talent Program - Translational Genome Analytics - Co-op
About The Position
The Research & Development Division Data, AI & Genome Sciences 2027 Future Talent Program is offering two computational co-op positions for a six-month term. The roles provide students with hands-on experience applying computational methods to drug-discovery questions, developing their skills, and evaluating longer-term fit with the team. Positions are based in Cambridge, Massachusetts; Boston, Massachusetts; or South San Francisco, California. Remote work may be considered. The Computational Oncology position analyzes and integrates large transcriptomic datasets to understand tumor biology and support target and biomarker discovery. Work may involve bulk and single-cell RNA-seq quality control, cell-type annotation, characterization of tumor and tumor-microenvironment cell states, relating molecular profiles to drug and therapy response, characterizing transcriptional responses to therapeutic perturbations, and producing reproducible analyses and visualizations for project teams. The Computational Immunology position applies computational methods to immune-profiling datasets to understand disease biology and immune responses and support target evaluation. Work may include analyzing immune-focused sequencing data to characterize immune cell states and changes across disease and treatment; analyzing, implementing, and visualizing methods for studying interactions among disease-relevant biological networks; and mining internal and external molecular databases to support therapeutic discovery, disease stratification, and biomarker identification. This is a full-time, six-month co-op for students currently enrolled in at least a bachelor's degree program in biological sciences, computational biology, bioinformatics, or a related quantitative field. Graduate students in MS or PhD programs are highly encouraged to apply. The role is hybrid, with remote work potentially considered. No relocation or travel is required, and visa sponsorship is not available.
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
- Graduate students in MS or PhD programs are highly encouraged to apply.
- Excellent academic achievement and analytical ability.
- Strong communication and interpersonal skills, with 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 their 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
