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2027 Spring Co-op Quantitative Pharmacology, Morristown, NJ

Sanofi

·

Sep 22, 2026

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Salary
$57 – $60
Location
Morristown, NJ, United States of America
Type
Full-time
Education
PhD
Visa
Not sponsored
Closing date
Today
Source
Workday

Description

Job Title: 2027 Spring Co-op Quantitative Pharmacology

  • Grade: Co-op

  • Location: Morristown, NJ

  • Duration: 6 months

About the Job

Looking to launch your career at the cutting edge of healthcare? Join Sanofi for a chance to develop with mentoring and guidance from inspirational leaders while helping to make an impact on the lives of countless people worldwide. We are seeking a highly motivated Spring Co-op to join our Quantitative Pharmacology team.

The Quantitative Pharmacology (QP) department is an integral part of the Translational Medicine Unit within Sanofi. We leverage model-informed drug development (MIDD), including population pharmacokinetic (PK) and pharmacodynamic (PD) approaches, to support optimal decision-making and accelerate programs across the full drug development continuum, from early discovery through late-stage clinical development. In addition, we actively explore the integration of artificial intelligence and machine learning (AI/ML) approaches to complement traditional pharmacometrics methods and enhance data-driven decision-making.

Ready to grow your skills while helping shape the future of healthcare? At Sanofi, you’ll be empowered to learn, ask questions, and bring your ideas to life – all while supported by inspiring mentors and collaborative teams.

About Sanofi

We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.

Main Responsibilities:

  • 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.

About You

Basic Qualifications:

  • 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. Students currently on CPT, OPT, or STEM OPT usually require future sponsorship for long term employment and do not meet the Internal requirements for this program unless eligible for an alternative long-term status that does not require company sponsorship.

  • 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.

Preferred Qualifications:

  • 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.

Why Choose Us

  • Bring the miracles of science to life alongside a supportive, future focused team.​

  • 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.​

  • Build your future with access to the latest tools, digital innovation, and continuous learning that keep you ahead of the curve.​​

Compensation

The salary range for this position is $57 -$60 USD hourly. All compensation will be determined commensurate with demonstrated experience.

#LI-Onsite 

#vhd 

Pursue progress, discover extraordinary

Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.

Sanofi US endeavours to make our career center accessible to any and all users. If you are experiencing difficulty and need assistance applying online, please call 1-866-SANOFI2 (1-866-726-6342) or click here



US and Puerto Rico Residents Only

Sanofi Inc. and its U.S. affiliates are Equal Opportunity employers committed to a culturally inclusive workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.

Skills

Machine LearningData Science

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