2027 Spring Co-op Quantitative Pharmacology, Morristown, NJ

Sanofi is an R&D-driven biopharmaceutical company focused on developing medicines and vaccines to improve people’s lives. The Spring Co-op will support the Quantitative Pharmacology team by developing and applying quantitative, mathematical, and statistical models and simulations, including evaluating AI/ML techniques. The role also involves literature review, computational tool development, and implementation of modeling and simulation approaches.

What you'll do:

• The co-op will work closely with experienced scientists to develop and apply quantitative, mathematical, and statistical models and simulations. These efforts will contribute to the advancement of innovative methodologies, including the evaluation and application of AI/ML techniques where appropriate to complement mechanistic and statistical modeling approaches
• The candidate will be involved in a range of activities, including literature review, development of computational tools, and implementation of state-of-the-art modeling and simulation approaches within a quantitative framework. This may include exploring opportunities where AI/ML methods can augment pharmacometrics workflows, such as in data integration, predictive modeling, and model-informed decision support

What they're looking for:

• We are seeking a PhD candidate in statistics, biostatistics, biomedical engineering, applied mathematics, or a related quantitative discipline, who is advanced in their research program
• 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
• Must be enrolled in an accredited college or university throughout the duration of the co-op/internship
• Must be able to relocate to the office location and work 40hrs/week, Monday to Friday for the full duration of the co-op/internship
• Candidates should have a strong academic background in areas such as PK/PD, pharmacometrics, pharmaceutical sciences, applied mathematics, statistics/biostatistics, computational biology, or biomedical engineering
• Experience in data modeling, data science, data visualization, machine learning, and modern computational tools is highly desirable
• The ideal candidate will demonstrate the ability to work both independently and collaboratively within a multidisciplinary team environment

Benefits:

• Develop with mentoring and guidance from inspirational leaders
• Stretch your skills through apprenticeships, internships, graduate programs, and international experiences that grow with you.
• Learn from inspiring mentors and collaborative teams while contributing to real projects that shape the future of healthcare.
• Access to the latest tools, digital innovation, and continuous learning