Machine Learning Scientist, Oligo Research Intern

The Importance of the Role

Sarepta is expanding its capabilities in antisense oligonucleotide (ASO) therapeutics. As part of this initiative, we are integrating advanced machine learning (ML), artificial intelligence (AI), and data-driven modeling to accelerate ASO discovery and optimization. The Machine Learning Scientist, Oligo Research Intern will assist in developing a reproducible computational framework that enhances Sarepta’s AI/ML-assisted design pipeline for next-generation ASO therapeutics.

This role offers deep exposure to the drug development lifecycle, encompassing everything from data curation to model validation and tool deployment. The intern will gain hands-on experience in shaping the computational strategy behind future ASO designs.

The Opportunity to Make a Difference

In this internship, you will focus on developing sequence-aware predictive models to prioritize PMOs (phosphorodiamidate morpholino oligomers) based on their expected exon-skipping response. Additionally, the modeling framework will be extended to include PMO gapmers, siRNA–PMO hybrids, and ranking strategies for conjugate designs, significantly broadening the cross-modality design capabilities within Sarepta.

Key Responsibilities

• Develop and implement sequence‑aware machine learning models to prioritize ASO designs by predicted exon‑skipping response across multiple targets.
• Build a reproducible computational framework including data ingestion, feature engineering, model training, validation, and deployment for oligonucleotide design.
• Extend modeling and evaluation framework to PMO-gapmers, siRNA PMO hybrids, and conjugate designs to broaden cross‑modality capabilities.
• Curate and harmonize internal and external literature curated datasets and define robust sequence and structure features such as thermodynamics, accessibility, sequence motifs, secondary structure, and additional context that drive model performance.
• Establish benchmarks and prospective tests to assess accuracy, robustness, and scalability, and partner with experimental teams to validate predictions.
• Evaluate and adopt proprietary and open source tools to enhance modeling workflows and accelerate decision support.
• Maintain a clean and well‑documented codebase, and user guidance for cross‑functional teams.
• Perform additional related tasks as assigned.