AI/Machine Learning - Co-Op

Role Summary:

The Data Sciences team at Dyne Therapeutics is seeking an exceptional Co-Op candidate to contribute to development of machine learning (ML) and AI-driven tools for our R&D programs. The primary focus will be on refining molecular sequence-based ML models for property/activity prediction. This includes working with sequence, structural, and contextual features to enhance model performance and generalizability.

In addition, the Co-Op will contribute to development of LLM-based pipelines for scientific document drafting and evaluation, including retrieval-augmented generation (RAG) workflows to support internal research and regulatory processes.

This role provides hands-on experience at the intersection of computational biology and applied AI, directly supporting team priorities in molecular optimization, pipeline expansion, and AI capability development.

 

This role is based in Waltham, MA without the possibility of being remote. This is a 6-month position beginning in July.  

Candidates must be enrolled in an accredited college or university Co-Op Program.

 

 
Primary Responsibilities Include: 

• Support data curation, preprocessing, and feature generation for biomolecular sequence ML models.
• Assist with model training, evaluation, and benchmarking under guidance.
• Contribute to development and testing of LLM-based document drafting and verification pipelines.
• Deliver well-documented and reproducible code, analysis summaries, and a final presentation of contributions.

 Education and Skills Requirements: 

• Undergraduate or Graduate student currently pursuing a degree in bioinformatics, Computational biology, or computer science or equivalent experience. Must be in active student status during duration of Co-Op program.
• Demonstrated competency in python and/or R programming skills.
• Prior experience in data science, AI, or machine learning is preferred.
• Strong organizational skills and solid written and oral communication ability.

 

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