Pharma Engineering Co-op: CMC Synthetics & Process

Sanofi

Cambridge (MA)

Hybrid

USD 62,000 - 79,000

Full time

14 days+

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Job summary

Sanofi in Cambridge, MA invites a Spring Co-op in the CMC Synthetics Platform Process and Pharmaceutical Engineering team. You will bridge material science, process engineering, and computational modeling to understand how particle and crystal properties affect tablet manufacturability and drug product performance.

As a Master’s or PhD student, you’ll design experiments, run DIC imaging, and help build predictive tools for formulation and process design while gaining mentorship and real-world

Qualifications

  • Master’s or PhD in Chemical Engineering, Mechanical Engineering, Materials Science, Pharmaceutical Engineering, Biomedical Engineering, or related field.
  • Must be enrolled in an accredited college throughout the duration of the co-op/internship.
  • Must be permanently authorized to work in the U.S. without visa sponsorship.

Responsibilities

  • Predict and analyze single crystal material properties relevant to pharmaceutical development, including mechanical behavior and elastic properties.
  • Design and execute experimental studies to characterize tablet mechanical performance using diametral compression and dynamic breakage testing.
  • Use digital image correlation (DIC) and imaging tools to quantify strain localization and failure mechanisms.
  • Integrate experimental and modeling results to improve material-process-performance understanding.
  • Collaborate with scientists to translate findings into predictive frameworks for formulation and process design.

Job description

Sanofi in Cambridge, MA invites a Spring Co-op in the CMC Synthetics Platform Process and Pharmaceutical Engineering team. You will bridge material science, process engineering, and computational modeling to understand how particle and crystal properties affect tablet manufacturability and drug product performance.

As a Master’s or PhD student, you’ll design experiments, run DIC imaging, and help build predictive tools for formulation and process design while gaining mentorship and real-world

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