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Kickstart your career with a bioinformatics internship at Bristol Myers Squibb this summer 2026. This paid Summer Student Internship program provides a unique opportunity for students to apply computational biology, machine learning, and systems biology techniques to large-scale immuno-oncology datasets. As part of this life science internship, interns gain hands‑on experience in data‑driven drug discovery, collaborate with industry experts, and advance their professional skills in a dynamic research environment.
Bristol Myers Squibb (BMS) is a global biopharmaceutical company committed to discovering, developing, and delivering innovative medicines for patients with serious diseases. Focus areas include oncology, immunology, cardiovascular disease, and fibrosis. BMS provides a collaborative environment for student internships and early‑career scientists to gain hands‑on experience in cutting‑edge research. Their bioinformatics internships combine mentorship, real‑world exposure, and professional development opportunities, empowering students to contribute meaningfully to life science research while shaping their careers.
We are seeking a highly motivated student to join our early (preclinical) R&D group for a paid 10-week summer internship. The successful candidate will work with a mentor to apply algorithmic, statistical, systems biology, and data mining approaches to large-scale biological datasets to identify candidate gene combinations relevant to logic‑gated targeting. This internship provides a unique opportunity to gain experience in computational biology, immuno‑oncology, and data‑driven drug discovery within an industry setting. The full-time internship will take place from June to August 2026.
Bristol Myers Squibb is offering a 10‑week bioinformatics internship for PhD students in computational biology, bioinformatics, biostatistics, or related quantitative life sciences. Interns will work with mentors in the Predictive Biology and AI (PBAI) team to analyze single‑cell RNA sequencing and spatial transcriptomics data. The role involves identifying candidate gene combinations relevant to logic‑gated targeting and presenting findings to the Informatics and Predictive Sciences division.