Intern, Translational Data Science (Project: Characterizing Ovarian Cancer Regulatory Networks in the context of Therapeutic Target Biology)

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

Join our Translational Data Science team in Utrecht to work on a research project focused on ovarian cancer, a disease characterized by substantial molecular heterogeneity and variable response to targeted therapies. A key open question is how underlying gene regulatory networks define tumor states and whether these regulatory programs influence the expression and biology of clinically relevant targets such as FOLR1 (Folate Receptor 1).

In this project, you will investigate regulatory network architecture in ovarian cancer using multimodal network modeling approaches. You will analyze molecular data from ovarian cancer cohorts to reconstruct regulatory network modeling (e.g., PANDA, doi: 10.1093/bioinformatics/btx139 ) and identify coordinated transcriptional programs that define distinct tumor states. You will characterize these regulatory programs and assess how they relate to therapeutic targets expression and associated biological processes. This includes identifying key transcription factors, pathways, and tumor microenvironment features that may modulate or co-occur with the biology of therapeutic targets. The analysis will leverage both internal and public datasets, and findings will be evaluated for robustness across independent cohorts. Where relevant, results will be interpreted in the context of ongoing translational research efforts. This project will provide insight into the regulatory mechanisms shaping ovarian cancer biology and their potential impact on therapeutically relevant targets.

Does this sound like something that interests you? We look forward to receiving your application and exploring the possibility of you joining our team to contribute to the advancement of antibody therapeutics! Help us get to know you by submitting a CV and motivational letter.

Responsibilities

• Process and analyze ovarian cancer gene expression datasets from internal and public sources

• Construct gene regulatory networks using approaches such as PANDA

• Identify regulatory programs and transcriptional modules defining tumor states

• Characterize network modules using pathway and gene set enrichment analyses

• Investigate relationships between regulatory programs and the expression and biology of potential therapeutic targets

• Explore associations with broader biological features (e.g., tumor microenvironment, cellular states)

• Assess robustness and reproducibility of findings across independent datasets

• Generate clear visualizations and interpretable summaries of network-level results

• Document analysis workflows and present findings to different team

Requirements

• Currently enrolled in a Master’s degree program 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.

• Available for a minimum of 6 months.

• Strong interest in machine learning, network biology, and cancer research.

• Experience with R and/or Python for data analysis.

• Experience with version control (Git) and cloud-based environments (e.g., RStudio cloud and AWS) is preferred.

• Familiarity with gene expression analysis and/or network modeling methods is preferred.

• Basic understanding of cancer biology or immunology is a plus.

• Ability to translate computational findings into biological insights.
  

General Information

• Internship duration: 6-9 months.

• Start date: September 1st 2026.

• Location: Utrecht, Netherlands

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.