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!
The Role
Genmab is seeking a Data Scientist with experience in active learning and/or lab-in-the-loop approaches to join our Discovery Data Science department in Utrecht!
You will join a growing, multidisciplinary team of data scientists working closely with experimental scientists across the Discovery organization. Together, you will connect machine learning with laboratory experiments to better understand antibody function and the biological mechanisms underlying it. Your work will contribute to Genmab’s Digital Twin initiative and help build predictive capabilities that support antibody discovery.
In this role, you will develop and apply ML models that help teams decide what to test next, learn from the results, and refine their approach as new data become available. Working at the interface between data science and experimental biology, you will translate scientific questions into modelling strategies and help identify the experiments most likely to advance understanding and inform discovery decisions.
Alongside your project work, you will contribute to reusable analytical workflows and modelling tools that can be applied across future discovery programs. This role offers the opportunity to see how your models inform experimental work and how experimental findings, in turn, improve your models.
We recognize that candidates may bring different combinations of machine learning expertise and biological knowledge. If you meet the core requirements but do not have experience in every scientific area listed, we encourage you to apply.
Responsibilities
Collaborate with data scientists and experimental scientists to translate antibody discovery questions into clearly defined modelling objectives and approaches.
Experience in immune-oncology, antibody discovery, therapeutic protein research, or related areas is highly valued.
Develop, apply, and evaluate machine learning models using molecular and experimental data, with a focus on active learning and lab-in-the-loop approaches.
Work with laboratory scientists to design informative experiments and data-generation strategies for predictive modelling.
Analyze and integrate antibody discovery and screening data to inform molecule design, experimental strategy, and project decisions.
Refine models as new experimental results become available, assessing their predictive performance and biological relevance.
Build robust, reproducible analytical workflows and reusable modelling tools that support work across discovery programs.
Communicate modelling approaches, findings, and limitations clearly to colleagues across scientific and technical disciplines.
Take ownership of your data science contributions within multidisciplinary projects and identify new opportunities for machine learning to support discovery.
Requirements
To succeed in this role, you bring strong machine learning foundations, scientific curiosity, and an interest in working closely with experimental scientists. You also have:
A PhD in a relevant scientific or quantitative discipline, with demonstrated expertise in data science and machine learning.
Experience in immune-oncology, antibody discovery, therapeutic protein research, or related areas is highly valued.
Experience with active learning, lab-in-the-loop methodology, sequential experimental design, or closely related approaches.
Experience applying machine learning to biological, molecular, or experimental data, with the ability to interpret modelling questions and results in their biological context.
A strong foundation in statistics, model development, and rigorous evaluation, including an understanding of model uncertainty and limitations.
Strong programming skills in Python and experience with reproducible computational workflows, command-line environments, and Git.
Strong collaboration and communication skills, with the ability to connect biological questions, experimental approaches, and data science.
The ability to work independently on defined scientific problems while actively seeking input and sharing progress with colleagues.
Excellent written and spoken English, Genmab's primary language.
Availability to work 32–40 hours per week, including approximately 2–3 days per week at our offices in Utrecht.
You must already be based in the Netherlands at the time of application.
The proposed gross annual/monthly base salary range for this position, in the primary location, based on a full time schedule is:
EUR59.568,00---89.352,00
The final salary offer will depend on several factors, including your skills, qualifications, and experience.
In addition to base salary, this position is eligible for additional forms of compensation, such as discretionary bonuses and long-term incentives.
When you join Genmab, you become a part of a culture that supports your physical, financial, social, and emotional well-being. Our benefits include, but are not limited to:
- ✓Pension
- ✓Health insurance and wellness benefits
- ✓Paid time off
- ✓Employee support programs
Further details on eligibility for compensation and benefits based on the role will be provided during the recruitment process.
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.