Sanofi is committed to becoming the first biopharma to leverage AI at scale by harnessing the full value of data across our gene therapy pipeline. Our "iCMC Digital Transformation" initiative has been digitizing scientific workflows across 2,500+ users in 10+ countries, creating tremendous potential to transform our AAV vector development through data-driven approaches.
Requirements
- Good exposure with core data science languages (with Python, and R), Snowflake and other database systems (such as SQL, NoSQL).
- Ability to create visualizations using tools like Matplotlib, Seaborn, Plotly or Tableau to communicate insights effectively
- Proficient in navigating and utilizing Unix-based operating systems
- Familiarity with bioinformatics workflows and biological data analysis.
- Basic understanding of Knowledge Graphs and Large Language Models through coursework or research experience in Artificial Intelligence.
- Hands-on experience with data manipulation, statistical analysis, and machine learning applied to biological datasets
- Familiarity with machine learning algorithms and frameworks like TensorFlow, PyTorch, or scikit-learn
Responsibilities
- Perform exploratory data analyses using graph visualizations of AAV production data, focusing on producer cell line characteristics, transfection efficiency, vector yield, and quality attributes
- Create knowledge graphs connecting critical relationships between AAV process operations, parameters, and materials (e.g., plasmid quality, cell line attributes, transfection conditions, etc)
- Evaluate internal Large Language Models (LLMs) and develop fine-tuning approaches to enhance foundational models with AAV-specific knowledge graphs
- Demonstrate how combining knowledge graphs with generative AI can optimize AAV vector development through predictive modeling of process parameters and quality attributes
- Building on previous co-op infrastructure.
Other
- Currently working towards a PhD in computer sciences or engineering or Life Sciences/Bioprocess Engineering/Chemical Engineering with the expectation that you will complete your current degree by the spring of 2027.
- Must be able to relocate to the office location and work 40hrs/week, Monday-Friday, for the full duration of the co-op/internship
- Must be permanently authorized to work in the U.S. and not require sponsorship of an employment visa (e.g., H-1B or green card) at the time of application or in the future. Students currently on CPT, OPT, or STEM OPT usually require future sponsorship for long term employment and do not meet the requirements for this program unless eligible for an alternative long-term status that does not require company sponsorship
- Sufficient organizational skills paired with strong written and verbal communication skills to effectively collaborate with cross-functional teams
