2027 Spring Co op Process and CMC Data Science Waltham MA

Sanofi • Waltham, MA

6d • $35 - $60 • Onsite

About The Position

Sanofi is seeking a highly motivated Spring 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. The co-op will develop first-principle, machine-learning, and hybrid models for critical drug-substance unit operations—including In-Vitro Transcription (IVT), Tangential Flow Filtration (TFF), and Chromatography—to accelerate mRNA-based process development.

The role offers hands-on experience with mRNA technology and drug-substance manufacturing operations while applying advanced modeling techniques. The co-op will contribute to biopharmaceutical research at the intersection of data science and process engineering, working with a supervisor and cross-functional team members. The position lasts six months and requires 40 hours per week, Monday through Friday, at the office location.

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 U.S. and not require employment visa sponsorship at the time of application or in the future.
• Must be enrolled in an accredited college or university throughout the co-op/internship.
• 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/internship.
• Python proficiency is required.
• Strong written and verbal communication skills, with the ability to present technical results to diverse audiences.
• Minimum cumulative GPA of 3.0 on a 4.0 scale.

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 BOTorch or PYOMO.
• Experience with MATLAB or gPROMS.
• Experience with Julia.
• Experience with first-principle models, machine learning, chromatography optimization, or models for IVT, purification, and chromatography processes.
• Familiarity with Design of Experiments (DoE), uncertainty quantification, and Bayesian optimization.

Responsibilities

• Develop and validate first-principle, machine-learning, and hybrid models for drug-substance unit operations such as IVT, TFF, and Chromatography in collaboration with a supervisor and cross-functional team members.
• Investigate the impact of process parameters on critical quality attributes (CQAs) 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 that inform process development decisions.
• Document modeling workflows, results, and recommendations in clear technical reports and presentations.

Benefits

• Apprenticeships, internships, graduate programs, and international experiences.
• Access to the latest tools and digital innovation, and continuous learning.
• Salary range of $35.00–$60.00 per hour, commensurate with demonstrated experience.

What This Job Offers

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