Quantitative Systems Pharmacology (QSP) Modeling Intern | Princeton, NJ
Job ID: R14682
Category: Research & Discovery
Location: Princeton, New Jersey, United States
Job Type: Internship (June – August 2026, Hybrid)
About Genmab
Genmab is a global biotechnology leader dedicated to transforming patient care through innovative antibody therapeutics. For over 25 years, the company has developed next-generation platforms, including bispecific T-cell engagers, antibody-drug conjugates, immune checkpoint modulators, and effector function-enhanced antibodies.
With a presence across North America, Europe, and Asia-Pacific, Genmab’s mission is to deliver Knock-Your-Socks-Off (KYSO®) antibody medicines that advance the future of oncology and serious disease treatment.
Learn more at www.genmab.com.
Internship Overview
The QSP Modeling Intern will join Genmab’s Quantitative Systems Pharmacology team to gain hands-on experience in mechanistic modeling supporting oncology drug discovery and development. The intern will build computational models to understand disease biology, pharmacokinetics/pharmacodynamics (PK/PD), and drug mechanisms of action for antibody therapeutics.
This is a hybrid internship requiring 3 days onsite in Princeton, NJ, and 2 days remote per week.
Key Responsibilities
Develop and apply mechanistic models to support QSP projects in oncology.
Perform simulations and analyses to evaluate system behavior and treatment responses.
Integrate preclinical and literature-derived data to inform model structure and parameterization.
Visualize and interpret model outputs to generate actionable insights supporting hypothesis testing and experimental design.
Collaborate with multidisciplinary teams to align modeling objectives with project needs.
Document modeling workflows, assumptions, and findings clearly and reproducibly.
Communicate results effectively to cross-functional teams.
Required Qualifications
Currently enrolled in a PhD program in engineering, applied mathematics, systems biology, pharmaceutical sciences, or a related quantitative discipline.
Strong experience with MATLAB and SimBiology for model development and simulation.
Solid understanding of differential equations, reaction kinetics, and quantitative biological systems modeling.
Demonstrated ability to analyze complex datasets and extract mechanistic insights.
Excellent communication and collaboration skills in multidisciplinary settings.
Self-motivated, detail-oriented, and strong problem-solving capability.
Preferred Qualifications
Familiarity with PK/PD modeling and systems pharmacology frameworks.
Experience modeling biological pathways or cellular dynamics relevant to oncology or immunology.
Publication or presentation experience in computational modeling, systems biology, or pharmacometrics.
Internship Benefits
Hands-on experience in advanced computational modeling in oncology.
Exposure to preclinical and clinical translational research.
Networking opportunities with experienced scientists and multidisciplinary teams.
Insight into cutting-edge antibody therapeutic development.
About You
Passionate about quantitative modeling and oncology research.
Collaborative and adaptable in a fast-paced, innovative environment.
Detail-oriented, proactive, and solution-focused.
Committed to excellence and continuous learning.
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