2027 Spring Co-Op Quantitative Pharmacology, Morristown, NJ

RippleMatch Inc.; Morristown (NJ); On-site; USD 48,216 - 75,768; Full time

Job summary

Sanofi in Morristown, NJ is seeking a Spring 2027 Co-Op in Quantitative Pharmacology to apply mathematical modeling that predicts how medicines behave in the human body, accelerating discovery to patient delivery.

This six-month program offers mentorship, exposure to an AI-powered biopharma environment, and the chance to learn from teams focused on innovative therapies while contributing to real projects shaping the future of healthcare.

Qualifications

• Master's or PhD degree in Statistics, biostatistics, biomedical engineering, applied mathematics.
• Candidates must also meet the following eligibility requirements.
• 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.

Responsibilities

• Use mathematical modeling to predict how medicines behave in the human body, accelerating the path from discovery to patient.

Education

Master's or PhD degree in Statistics, biostatistics, biomedical engineering, applied mathematics

Job description

2027 Spring Co-Op Quantitative Pharmacology, Morristown, NJ

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.

This co-op opportunity will have a 6 month duration starting January 2027.

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.

Available Disciplines

• Quantitative Pharmacology (PKDM): Use mathematical modeling to predict how medicines behave in the human body, accelerating the path from discovery to patient.

About You

Basic Qualifications:

Currently enrolled at an accredited college or university pursuing a:

• Master's or PhD degree in Statistics, biostatistics, biomedical engineering, applied mathematics

Candidates must also meet the following eligibility requirements:

• 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.

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.

• Explore more with personalized development plans, short-term gigs, and internal mobility across functions and countries.

• Grow in a purpose-driven company where your voice matters and your work helps improve millions of lives.

• Thrive in inclusive, flexible workplaces that support your personal and professional well-being.

• Launch your career with a company that invests in you — and empowers you to reimagine what's possible.

Compensation

The salary range for this position is: $35 - $55 hourly. Final compensation will bedeterminedbased ondemonstratedexperience, skills, location, and other relevant factors.