Summer 2025 Intern- Modeling and Simulation within PKDM

Key Skills

Aartificial intelligence, Apache Kafka, AWS, Azure, Machine learning techniques, R Programming, Tableau, UI design, UX design

Job Description

The Pharmacokinetics, Pharmacodynamics and Drug Metabolism (PKDM) department is an integrated part of the Translational Medicine and Early Development organization within Sanofi.

We use model-based drug development approach (e.g., population pharmacokinetic (PK)/pharmacodynamic (PD) ) to enable optimal decision-making in accelerating programs across pipelines from earliest to late stage of drug development. The co-op will learn about clinical pharmacology and pharmacometrics, including principles of model-based drug development in pharmaceutical R&D settings. The co-op will work closely with our staff to develop and apply quantitative mathematical/statistical models and simulations contributing to the development and implementation of new capabilities, standards, and approaches. He/she will be involved in various activities to support clinical development programs including medical literature review, development of computer programs or state-of-the-art quantitative methodologies within the modeling and simulation framework.

At this time, Sanofi will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization). 

Basic Qualifications:

• Must be currently pursuing a PhD in Biomedical Engineering, Computer Science, Electrical Engineering, Chemical Engineering, Computer Engineering, Applied Mathematics, Mechanical Engineering, or related field.

• Must be enrolled in school the semester following your internship/co-op with Sanofi. 

• Must be able to relocateto theoffice location and work 40 hrs./week for the full duration of the internship/Co-op

• Must have permanent US work authorization

Preferred Qualifications:

• Must be detail-oriented, highly organized, and able to manage multiple tasks.

• Must have the ability to work individually as well as on a team.

• The co-op will be based within the PKDM group at Sanofi, Bridgewater, NJ (USA) on full-time basis.

• Experience in data modeling, data science, data visualization, machine learning with computing technologies are highly desirable.

At Sanofi R&D North America, we deliver meaningful solutions for patients. We transform science into breakthrough, best-in-class and first-in-class medicines and vaccines. We believe in creating a diverse and inclusive workforce – and workplace – which brings together the collective brainpower of over 2,000 colleagues and provides you with an exciting place to grow and develop. We set the bar high, and we deliver. Join us and together we will build on our trusted legacy of breakthroughs for society.

Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse 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.​

Pursue progress. Discover extraordinary.

• 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. You can be one of those people. Chasing change, embracing new ideas and exploring all the opportunities we have to offer. Let’s pursue progress. And let’s discover extraordinary together.

• At Sanofi, we provide equal opportunities to all regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.