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!
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.
The Role
Are you excited about using computational biology to better understand how cancer evolves after treatment? As an intern in our Discovery Data Science team, you will contribute to building a single-cell cancer landscape of treated patients. While single-cell RNA sequencing (scRNA-seq) has been widely used to map tumor biology, most published studies focus on treatment-naïve samples. In contrast, patients entering experimental therapies are often heavily pre-treated, and their tumors may differ significantly at the cellular and molecular level.
In this project, you will use large language models (LLMs) and internal harmonized single-cell datasets to identify treated patient samples across studies. You will then harmonize and integrate these datasets to generate a unified single-cell landscape of treated tumors. Using established computational methods (such as SCVI), you will explore treatment-associated biology through analyses such as cell type abundance (using Milo package), trajectory and pseudotime modeling (Slingshot, PAGA and Monocle packages), gene network analysis, and cell–cell communication inference (Cell Phone DB and CellChat packages).
There are multiple directions this project can take depending on your background and interests, meaning you will have the opportunity to shape the focus in line with your skills and your university’s requirements. Ultimately, your work will contribute to a deeper understanding of tumor biology after treatment and help inform data-driven target discovery strategies in oncology!
Responsibilities
Identify and curate treated patient samples from internal harmonized single-cell datasets using LLM-supported approaches.
Harmonize and integrate single-cell RNA sequencing datasets across studies.
Perform downstream analyses including cell type abundance, trajectory and pseudotime analysis, gene network analysis, and cell–cell communication modeling.
Evaluate and benchmark internally developed and publicly available computational methods.
Interpret results in close collaboration with computational and biological scientists.
Present findings through reports and internal presentations.
Requirements
Currently enrolled, throughout the course of this internship, in a Bachelor’s or Master’s program in Bioinformatics, Computational Biology, Data Science, Computer Science, or a related field at a Dutch university.
This internship must be a formal, mandatory component of your degree program required for graduation; we cannot consider candidates who have already graduated or who are seeking an extracurricular internship.
Experience with Python and/or R.
Strong interest in computational biology and high-dimensional data analysis.
Basic understanding of molecular biology and cancer biology.
Ability to work independently while collaborating in a multidisciplinary team.
Experience working with single-cell RNA sequencing data.
Familiarity with machine learning or natural language processing (e.g., LLMs).
Experience with data integration or multi-dataset harmonization.
Strong analytical thinking and attention to detail.
Clear communication skills in English, as it’s Genmab’s primary language.
General Intern Information
Internship duration: 7 - 10 months
Start date: September 1st, 2026 (flexible)
Location: Utrecht, Netherlands
This is a fulltime hybrid internship position (on average 3 days onsite, 2 days from home).
Intended Recruitment Timeline
Application deadline: Monday 6 April (end of day)
Shortlisting: week of 6 April
Virtual screenings: weeks of 13 & 20 April
Onsite interviews: week of 27 April / 4 April
What’s Next?
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!
About 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!
Locations
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.
About Genmab
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).
Please note that if you are applying for a position in the Netherlands, Genmab’s policy for all permanently budgeted hires in NL is initially to offer a fixed-term employment contract for a year, if the employee performs well and if the business conditions do not change, renewal for an indefinite term may be considered after the contract.