2027 Spring Co op Biologics Design and AI
Sanofi
Cambridge, MAFresher2h agovia LinkedIn
Posted 14 Nov 2026, 13:00 ET
This job at a glance
- Who can apply
- New grads and up to 1 year
- Must know
- NLPLLMsSpringPythonDeep learningPyTorch
- Work
- On-site in Cambridge
- Pay
- Not stated by the employer.
- Skill demand
- Python28%LLMs27%Spring12%NLP7%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 14, 2026 · still open
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About the Role
Join Sanofi for a 6-month co-op position in Biologics Design and AI in Cambridge, MA. This role offers mentoring and guidance from leaders, with the opportunity to develop at the cutting edge of healthcare.
Main Responsibilities
- LLM Fine-Tuning & Cross-Modal Adaptation: Fine-tune conversational, natural language LLMs to interface with and reason over data from specialized protein prediction models. Adapt LLMs to comprehend protein sequences, structural embeddings, and biophysical constraints using parameter-efficient techniques (e.g., LoRA, PEFT). Build hybrid architectures to enhance predictions of antibody and nanobody properties.
- Collaboration & Reporting: Partner with experimental protein engineers and computational biologists. Validate model predictions and present methodologies, insights, and model performance to cross-functional R&D teams.
Requirements & Tech Stack
- Currently pursuing a Master’s or PhD degree in Computer Science, Data Science, Computational Biology, Bioinformatics, Bioengineering, or related field, graduating by Spring 2027 (or 2028).
- Permanently authorized to work in the U.S. without requiring visa sponsorship (e.g., H-1B, green card).
- Enrolled in an accredited college or university throughout the co-op duration.
- Ability to relocate to Cambridge, MA and work 40 hours/week, Monday to Friday, for the full co-op term.
- Strong programming skills in Python and standard data science libraries.
- Experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Experience using state-of-the-art AI tools for biology (e.g., Protein LLMs, AlphaFold, Rosetta).
- Fluent in English.
Qualifications
- Previous academic projects or industry experience demonstrating the application of NLP, LLMs, or agentic workflows to complex scientific problems.
- Familiarity with biological data, specifically protein sequences and 3D structures.
- Basic domain knowledge in immunology, structural biology, or biophysics.
- Hands-on experience with LLM fine-tuning methodologies and orchestration frameworks.
- Excellent problem-solving and communication skills, with a passion for working at the intersection of generative AI and healthcare.
Compensation
- $47 - $60 hourly. Compensation determined commensurate with demonstrated experience.