Clinical Development Data Science Intern

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!

Clinical Development Data Science Intern

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.

The Clinical Development Data Science Intern will join Genmab’s Clinical Development Data Science team and contribute to innovative AI/ML initiatives across the clinical development lifecycle. This role is ideal for a highly technical, impact-driven data scientist who is pursuing a Master's or PhD in a quantitative or computational discipline, and who is excited to apply modern machine learning, natural language processing, and generative AI to real clinical and scientific challenges in oncology.

The intern will support projects such as building AI-powered tools to assist trial design, developing analytics pipelines for clinical and safety data, and prototyping advanced models that help clinicians and scientists make better, faster decisions. You will collaborate with experienced data scientists, data engineers, clinicians, and other cross-functional partners to deliver meaningful analyses, prototypes, and decision-support tools used across clinical development.

• Develop machine learning and NLP pipelines to extract, organize, and summarize information from clinical trial protocols, regulatory documents, and unstructured biomedical text.

• Support the development of AI-driven tools that:

  • Accelerate protocol design through information retrieval, extraction, and summarization.

  • Enhance pharmacovigilance and safety monitoring through risk modeling, anomaly detection, and severity prediction.

• Apply advanced modeling techniques including transformers, generative models, survival analysis, clustering, and other ML approaches.

• Experiment with explainability methods (e.g., SHAP, LIME) to improve the interpretability of models used in clinical decision-support contexts.

• Contribute to documentation, model evaluation, technical reviews, and final presentations to internal stakeholders.

• Sustained progress in a PhD program in a quantitative or computational discipline (Computer Science, Data Science, Statistics, Physics, Computational Chemistry, Computational Biology, Applied Mathematics, Engineering, or related quantitative/technical field).

  • Master’s students with strong applied experience will also be considered.

• Strong proficiency in modern Python for machine learning and scientific computing (e.g., PyTorch/TensorFlow, scikit-learn, spaCy, Hugging Face transformers, pandas, NumPy).

  • Candidates should be experienced in building modular scripts and reusable modules, command-line utilities, and structured codebases for data processing and machine learning workflows.

• Experience applying ML or NLP methods to real-world datasets.

• Ability to design, build, and evaluate computational models end-to-end.

• Excellent analytical problem-solving abilities and intellectual curiosity.

• Clear written and verbal communication skills.

• High attention to detail, scientific rigor, and commitment to producing high-quality work.

• Ability to work independently as well as collaboratively within interdisciplinary teams.

• Experience with large language models, retrieval-augmented generation (RAG), or generative AI workflows.

• Prior work involving unstructured document parsing (e.g., PDFs, scanned text, scientific literature).

• Full-stack data science skill set, including experience with:

  • Writing production-quality, modular, and reusable Python code

  • Building scalable, reproducible systems and packaging code for broader use

  • Containerization (e.g., Docker) and reproducible compute environments

  • Workflow or pipeline orchestration tools (Airflow, Prefect, Dagster, etc.)

  • Cloud computing environments (AWS, Azure, GCP)

• Experience using Git repositories and version-control workflows, including:

  • Branching strategies, pull requests, peer code reviews

  • Good commit hygiene and collaborative development practices

  • Familiarity with GitHub, GitLab, or similar platforms

• Exposure to CI/CD, structured logging, automated testing, or other professional engineering practices.

• Experience with MLOps concepts such as model packaging, monitoring, reproducibility, and deployment is a strong plus.

Internships will take place June – August 2026. This role will be based in Princeton, NJ, and operate on a required hybrid schedule – 3 days in the office and 2 days remote per week.

Help us learn about you by submitting a complete and thoughtful application, which includes your resume. Your application and resume are a way for us to initially get to know you, so it’s important to complete all relevant questions to ensure we have as much information about you as possible.

Every application matters to us, and we’ll carefully review each submission as quickly as possible to see if your qualifications align with the role. While we’re unable to provide individual updates, rest assured that we’re working diligently to move through the process efficiently.

If you move forward in the process, you’ll receive an email invitation to connect with us and dive deeper into this exciting opportunity. The final stage will bring selected candidates meeting directly with our hiring teams, where you’ll have the chance to showcase your potential. We are committed to keeping you informed and will share decisions with all candidates as soon as we are able.

We can't wait to see where this journey takes you!

• You are genuinely passionate about our purpose

• You bring precision and excellence to all that you do

• You believe in our rooted-in-science approach to problem-solving

• You are a generous collaborator who can work in teams with a broad spectrum of backgrounds

• You take pride in enabling the best work of others on the team

• You can grapple with the unknown and be innovative

• You have experience working in a fast-growing, dynamic company (or a strong desire to)

• You work hard and are not afraid to have a little fun while you do so!

Genmab maximizes the efficiency of an agile working environment, when possible, for the betterment of employee work-life balance. Our offices are crafted as open, community-based spaces that work to connect employees while being immersed in our powerful laboratories. Whether you’re in one of our office spaces or working remotely, we thrive on connecting with each other to innovate.

Genmab is an international biotechnology company with a core purpose to improve the lives of patients through innovative and differentiated antibody therapeutics. For 25 years, its hard-working, innovative and collaborative team has invented next-generation antibody technology platforms and harnessed translational, quantitative and data sciences, resulting in a proprietary pipeline including bispecific T-cell engagers, antibody-drug conjugates, next-generation immune checkpoint modulators and effector function-enhanced antibodies. By 2030, Genmab’s vision is to transform the lives of people with cancer and other serious diseases with Knock-Your-Socks-Off (KYSO®) antibody medicines.

Established in 1999, Genmab is headquartered in Copenhagen, Denmark with international presence across North America, Europe and Asia Pacific. For more information, please visit Genmab.com and follow us on LinkedIn and X.

Genmab is committed to protecting your personal data and privacy. Please see our privacy policy for handling your data in connection with your application on our website Job Applicant Privacy Notice (genmab.com).