Intern, Translational Data Science; Project: Computational and Molecular Approaches

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!

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.

Are you excited about the intersection of AI and cancer immunology, looking to make a meaningful impact in the field of antibody therapeutics? Do you want to gain exposure to the strategic design of innovative antibody therapeutics? Keep on reading! We are seeking a highly motivated intern to join the Early Translational Data Science team, contributing to early risk assessment strategies s role will focus on harnessing molecular data to support data-driven decision‑making in early‑stage drug development and closing translational gaps between preclinical species (rat, non‑human primates) and humans.

An exciting, multidisciplinary project that combines Data Science, Molecular Biology and Toxicology!

• Process and analyze RNA‑seq data (bulk and single‑cell) from human, rat, and non‑human primate studies and retrieve/ingest new datasets.

• Build reproducible analysis pipelines (e.g., Python/R + notebooks) for cross‑species comparison.

• Analyze retrospective pre‑clinical data, compiling nonclinical toxicology endpoints (e.g., histopathology findings, clinical chemistry, exposure).

• Investigate cell‑/lineage‑specific expression and association with toxicological endpoints.

• Enable real time follow‑ups / additional analyses, such as cell‑cell interactions across different organs.

• Actively enrolled - throughout the duration of this internship - in a Master’s degree program at a Dutch university in Molecular Biology, Bioinformatics, Biomedical Sciences, or a related field.

• Available for a minimum of 6 months (up to 9 months).

• Proficiency in R programming, with a focus on producing clean, standardized, and well‑documented code.

• Familiarity with bioinformatics pipelines (e.g., gene expression analyses) and handling and manipulating large scale datasets.

• Experience working with public bioinformatics databases (e.g., GEO, TCGA).

• Familiarity with version control (e.g. Git).

• Basic knowledge of translational research in cancer biology; familiarity with single‑cell data or toxicology is a plus.

• Comfortable working collaboratively in a multidisciplinary team.

• Proven creativity, analytical thinking, strong organizational skills, and a collaborative spirit.

• Internship duration: 6-9 months.

• Start date:
  
  February/March 1st.

• Location:
  
  Utrecht, Netherlands.

• This is a fulltime hybrid internship position.

Help us learn about you by submitting a complete and thoughtful application, which includes your CV and motivation letter. These 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.

We look forward to receiving your application and exploring the possibility of you joining our team to contribute to the advancement of antibody therapeutics.

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