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!

REQUIREMENTS

• MSc degree (or BSc with equivalent experience) in bioinformatics, data science, computational biology, or a related field.
• 2–5 years of relevant experience in research, academic, or industry setting (data science or bioinformatics).
• Recent graduates (with suitable internships) or candidates with <2 years of experience are also welcome to apply.
• Solid programming experience in R, especially for Shiny application development.
• Familiarity with Python and/or single-cell RNA-seq workflow design.
• Experience with data curation and integration of public datasets.
• Exposure to modular code design, R package development, or workflow testing.
• Experience with RMarkdown, tidyverse (e.g., dplyr, ggplot2), and Git.
• Experience with GenAI or LLM-based summarization for knowledge extraction from scientific text.
• Experience working with genomics data, particularly bulk RNA-seq and single-cell RNA-seq.
• Basic knowledge of cancer biology or immunology.
• Understanding of preclinical research and translational workflows.
• Ability to design user-friendly, maintainable tools tailored to scientific use cases.
• Strong communication skills, including experience communicating genomics data to wet-lab scientists.
• Team player with excellent interpersonal skills and fluency in English (Dutch is not required).
• Able to work independently at the task level, with comfort working under project-level guidance.

THE ROLE

Genmab is currently seeking a (Senior) Research Associate in Translational Data Science, based in our Utrecht office in the Netherlands. This is a 6-month temporary position to support key tooling and infrastructure development within the Translational Data Science team, which is part of the Translational & Quantitative Sciences (TQS) organization.
You will join a multidisciplinary, international team of scientists dedicated to accelerating the translation of early research into clinical impact. In this role, your primary focus will be on extending and improving our internal Target Evaluation for Drug Development Shiny application, a tool developed in close collaboration with the Non-Clinical Safety (NCS) department. The application supports preclinical decision-making by integrating diverse data sources to inform target evaluation from multiple perspectives. You will incorporate additional features powered by Generative AI (GenAI), with a focus on generating summaries and extracting key insights from large datasets and textual sources relevant to target evaluation.
In addition, you will contribute to the optimization of internal pipelines, tools, R-based notebooks, and packages. This includes identifying opportunities to harmonize data sources, streamline analysis workflows, and build reusable tooling that supports consistent data interpretation across research programs. You will also support efforts to build internal data resources by curating and integrating public datasets, including bulk and single-cell RNA sequencing data, to enable downstream analysis within the team.
Under the guidance of a senior data scientist, you will collaborate closely with colleagues across TQS to gather requirements, implement features, and deliver tools that strengthen Genmab’s translational research capabilities.

RESPONSIBILITIES

• Extend and maintain internal R/Shiny applications, with a focus on the Target Evaluation for Drug Development tool developed in collaboration with the Non-Clinical Safety team.
• Integrate Generative AI (GenAI) functionality to summarize and extract insights from large datasets and textual sources.
• Collaborate with scientific stakeholders to gather requirements and translate them into functional tool specifications.
• Support data curation efforts, including the in-housing and structuring of public bulk and single-cell RNA-seq datasets.
• Optimize internal pipelines, notebooks, and R packages to improve reproducibility and harmonization of analysis workflows.
• Ensure version-controlled, modular, and reusable code across projects.
• Present tools and updates in cross-functional settings and refine based on user feedback.