2026 Future Talent Program - Representation Learning - Intern

Merck • Cambridge, MA

1d • Hybrid

About The Position

The Future Talent Program features internships that last up to 12 weeks and will include one or more projects. These opportunities in our Global Support Functions Division can provide you with great development and a chance to see if we are the right company for your long-term goals.
We are seeking a highly motivated intern with a background in molecular representation of small molecules. This interdisciplinary role is ideal for a student who can commit to 10–12 weeks internship starting in June 2026 and is excited to contribute to drug discovery and development. The intern will collaborate closely with data scientists, machine learning engineers, and bench scientists to advance our discovery and development process. Your work will focus on creating and improving models that support our discovery and development pipeline. This experience will be instrumental in learning how representation learning can be applied to small‑molecule drug discovery and development.

Requirements

• Current Ph.D. student focused on Computer Science, Data Science, Computational Chemistry, or Computational Structural Biology.
• Experience with deep learning frameworks, including Graph Neural Network (GNN) architectures and their applications in drug discovery and development.
• Proficiency in Python, RDKit, PyTorch, JAX, and TensorFlow.
• Solid knowledge of machine learning workflows, including version control (Git), model deployment, and basic UI/UX principles.
• Excellent problem‑solving skills, clear communication abilities, and strong collaboration skills across cross-functional scientific teams.
• Proven ability to thrive in fast‑paced and dynamic research environments.

Responsibilities

• Contribute to machine learning workflows, including data processing, model development, benchmarking, and refinement.
• Create visualizations and presentations summarizing key findings and present them in meetings.
• Collaborate with data scientists, computational chemists, and bench scientists.
• Contribute to documentation and reproducible workflows.
• Stay updated on new methods and technologies in molecular representation.

What This Job Offers

• Career Level: Intern
• Education Level: Ph.D. or professional degree