2027 Spring Co op Process and CMC Data Science Waltham MA

Sanofi • Waltham, MA

5d • Onsite

About The Position

Sanofi is seeking a highly motivated Spring 2027 co-op to join the Process and CMC Data Science team in the Data and Computational Science department within its mRNA Center of Excellence in Waltham, Massachusetts. This six-month position focuses on developing first-principle, machine-learning, and hybrid models for critical mRNA drug-substance unit operations, including In-Vitro Transcription (IVT), Tangential Flow Filtration (TFF), and chromatography. The co-op will gain hands-on experience with mRNA technology and drug-substance manufacturing while applying advanced modeling techniques to support process development.

The role involves investigating relationships between process parameters and critical quality attributes, quantifying uncertainty, and using experimental and simulation data to inform development decisions. The co-op will collaborate with a supervisor and cross-functional colleagues and document findings through technical reports and presentations. The position requires working onsite in Waltham, 40 hours per week, Monday through Friday, for the full six-month term.

Requirements

• Pursuing a master's or PhD in Chemical Engineering, Biochemical Engineering, Biochemistry, Data Science, Computer Science, Biomedical Engineering, Applied Mathematics, Analytical Chemistry, Physics, Software Engineering, or a related quantitative field at an accredited college or university.
• Must be permanently authorized to work in the United States and not require employment visa sponsorship at the time of application or in the future.
• Must remain enrolled in an accredited college or university throughout the co-op.
• Must be able to relocate to the office location and work 40 hours per week, Monday through Friday, for the full duration of the co-op.
• Python proficiency is required.
• Minimum cumulative GPA of 3.0 on a 4.0 scale.
• Strong written and verbal communication skills, including the ability to present technical results to diverse audiences.

Nice To Haves

• Foundational knowledge of mRNA technology or biopharmaceutical manufacturing processes.
• Experience developing physics-informed or physics-constrained machine-learning, first-principle, or hybrid dynamic models for physical or biological systems.
• Experience with modeling and programming tools such as BoTorch, Pyomo, MATLAB, Julia, or gPROMS; MATLAB and gPROMS are identified as nice to have.
• Experience with first-principle models, machine learning, chromatography optimization, or ML models for IVT, purification, or chromatography processes.
• Familiarity with Design of Experiments, uncertainty quantification, and Bayesian optimization.

Responsibilities

• Develop and validate first-principle, machine-learning, and hybrid models for drug-substance unit operations, including IVT, TFF, and chromatography, in collaboration with a supervisor and cross-functional team members.
• Investigate the impact of process parameters on critical quality attributes and quantify associated uncertainties using statistical and computational methods.
• Design and execute Design of Experiments (DoE) for model structure selection, parameter estimation, and process optimization.
• Analyze experimental and simulation data to generate actionable insights for process development decisions.
• Document modeling workflows, results, and recommendations in technical reports and presentations.

Benefits

• Mentoring and guidance from experienced leaders.
• Apprenticeships, internships, graduate programs, and international experiences for skill development.
• Access to tools, digital innovation, and continuous learning.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern