2027 Future Talent Program - AI/ML Biomedical Imaging and Computational Pathology - Intern

MSD • Cambridge, MA

6d • $39,908 - $111,111 • Hybrid

About The Position

The Future Talent Program within the Research & Development Division’s Data, AI, and Genome Sciences (DAGS) Department offers internships lasting 10–12 weeks. The intern will join the AI/ML imaging group and contribute to developing next-generation computational approaches for biomedical imaging and computational pathology. The project is intended to help students develop their skills and explore whether the company aligns with their long-term goals.

The AI/ML team develops methods to accelerate drug target and biomarker discovery. The intern will develop and apply foundation model-based AI methods to extract biologically meaningful, generalizable representations from histopathology images and spatial omics; design interpretable approaches for characterizing model representations using biologically grounded features; and integrate image-derived features with patient outcome and molecular data to support biological hypothesis generation and biomarker discovery. The intern will collaborate with colleagues in data science, computational pathology, biology, and translational research.

This is a full-time, 9–12-week internship beginning in May or June 2027. The position is hybrid. No relocation or travel is provided or required.

Requirements

• Currently enrolled in a PhD program in Computer Science, AI/ML, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related field.
• Available to work full-time for 9–12 weeks beginning in May or June 2027.
• Proficiency with Python programming and modern deep learning frameworks such as PyTorch.
• Strong communication and interpersonal skills, and ability to work well in a collaborative team environment.

Nice To Haves

• Familiarity with one or more of the following: computer vision, natural language processing, representation learning, foundation models, interpretable/explainable AI, and generative AI.
• Experience with biomedical or scientific data types, such as medical imaging, genomics, spatial omics, or clinical datasets.
• Track record of scientific communication, such as publications or conference presentations.

Responsibilities

• Develop and apply foundation model-based AI methods to extract biologically meaningful and generalizable representations from histopathology images and spatial omics.
• Design interpretable computational approaches to characterize model representations using biologically grounded features, such as morphological patterns and tumor microenvironment architecture.
• Integrate image-derived features with patient outcome and molecular data to support biological hypothesis generation and biomarker discovery.
• Collaborate with a multidisciplinary team spanning data science, computational pathology, biology, and translational research.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: Ph.D. or professional degree