2027 Future Talent Program - Translational Genome Analytics - Co-op

MSD • San Diego, CA

2d • Hybrid

About The Position

The Research & Development Division’s Data, AI & Genome Sciences Department is offering two computational co-op positions for a six-month term. These roles provide students with hands-on experience applying computational methods to drug-discovery questions, developing their skills, and allowing the student and team to evaluate longer-term fit. The positions are full-time and may be based in Cambridge, Massachusetts; Boston, Massachusetts; or South San Francisco, California. Remote work may be considered.

The Computational Oncology role analyzes and integrates large transcriptomic datasets to understand tumor biology and support target and biomarker discovery. Work may include bulk and single-cell RNA-seq quality control, cell-type annotation, characterization of tumor and tumor-microenvironment cell states, connecting molecular profiles with drug and therapy response, evaluating transcriptional responses to therapeutic perturbations, and creating reproducible analyses and visualizations for project teams.

The Computational Immunology role applies computational methods to immune-profiling datasets to understand disease biology and immune response 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.

Applicants must be currently enrolled in at least a bachelor’s degree program in biological sciences, computational biology, bioinformatics, or a related quantitative field, and available to work full-time for six months. Students in MS or PhD programs are highly encouraged to apply. The salary range is $39,908–$111,111. The position is an intern/co-op fixed-term role. Relocation, visa sponsorship, and travel are not provided or required. Flexible work arrangements are listed as hybrid.

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

• Enrollment in a graduate program (MS or PhD); graduate students are highly encouraged to apply.
• Excellent academic achievement and analytical ability.
• Strong communication and interpersonal skills and 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.
• 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 prioritize and evaluate candidate targets.
• Characterize transcriptional responses to therapeutic perturbations to inform mechanism 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern