Quantitative Systems Pharmacology (QSP) Modeling Intern

Genmab • Princeton, FL

8d • Hybrid

About The Position

At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking, knock-your-socks-off KYSO antibody medicines® that change lives and the future of cancer treatment and serious diseases. We strive to create, champion and maintain a global workplace where individuals’ unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees. Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science. We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose. Yes, our work is incredibly serious and impactful, but we have big ambitions, bring a ton of care to pursuing them, and have a lot of fun while doing so. Does this inspire you and feel like a fit? Then we would love to have you join us! Job Title Quantitative Systems Pharmacology (QSP) Modeling Intern Why Genmab Our internship program provides interns with hands-on experience and relevant projects that directly align with our company’s goals. Additionally, we believe our program provides a valuable opportunity to learn, thrive, and build a strong network. We encourage you to review our website to learn why we’re always looking for smart, purpose-led candidates to play a role in our bold, extra[not]ordinary® future. Job Overview Genmab’s Quantitative Systems Pharmacology (QSP) team is seeking a motivated and talented PhD-level intern to contribute to the development and application of mechanistic models supporting our oncology drug discovery and development programs. The intern will gain hands-on experience building computational models to understand disease biology, pharmacokinetics/pharmacodynamics (PK/PD), and drug mechanisms of action for antibody-based therapeutics. This position offers the opportunity to work alongside experienced scientists in a collaborative, multidisciplinary environment, applying advanced modeling tools to generate actionable insights that guide experimental design and decision-making across preclinical and clinical stages.

Requirements

• Currently enrolled in a PhD program in engineering, applied mathematics, systems biology, pharmaceutical sciences or related quantitative discipline.
• Strong experience with MATLAB and SimBiology for model development and simulation.
• Solid foundation in 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 with strong attention to detail and problem-solving ability.

Nice To Haves

• Familiarity with pharmacokinetic/pharmacodynamic (PK/PD) modeling concepts 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.

Responsibilities

• Contribute to quantitative systems pharmacology (QSP) projects by developing, adapting, or applying mechanistic models to address key research questions in oncology.
• Perform simulations and analyses under various biological or experimental conditions to explore system behavior and treatment responses.
• Integrate preclinical and literature-derived data to inform model structure, parameterization, and evaluation.
• Visualize and interpret model outputs to generate insights that support hypothesis generation or experimental design.
• Collaborate with scientists across disciplines to ensure alignment between modeling objectives, available data, and project needs.
• Document modeling workflows, assumptions, and findings in clear and reproducible formats, and communicate results effectively to cross-functional teams.

What This Job Offers

• Career Level: Intern
• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees