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

Are you excited about the intersection of AI, cancer immunology, and data science? Do you want to play a pivotal role in designing innovative deep learning models to extract radiomic features, with the ultimate aim of advancing antibody therapeutics and personalized cancer therapies? Join our Translational Data Science team in Utrecht and be at the forefront of integrating medical imaging with genomic data to identify actionable biomarkers.

You will contribute to a cutting-edge project where you will explore advanced deep learning techniques to analyze clinical imaging datasets such as CT and MRI scans. Your work will focus on designing and refining novel neural network architectures that extract quantitative features reflecting tumor heterogeneity. These features will be correlated with genomic alterations, such as KRAS or EGFR mutations, and clinical outcomes, informing targeted treatment strategies for lung cancer datasets like those from TCGA and validated on external datasets such as Lung NLST.

Responsibilities

Deep Learning Architecture & Radiomic Feature Extraction

• Design, implement, and optimize convolutional neural network (CNN)-based or similar deep learning models to extract high-quality radiomic features from medical imaging data.

Advanced Feature Integration & Analysis

• Investigate how deep learning–derived radiomic features correlate with specific genetic mutations or molecular subtypes and integrate these signatures with other omics data when available.

Model Validation & Robustness

• Apply best practices in cross-validation, perform hyperparameter tuning, and validate models on external datasets to ensure reproducibility and reliability in predicting cancer outcomes.

Innovation & Exploration

• Explore cutting-edge methods such as attention mechanisms and self-supervised learning to enhance the predictive power and generalizability of the models.

Collaboration & Communication

• Work collaboratively with computational biologists, bioinformaticians, and clinicians to drive project success, presenting findings in team meetings and documenting progress through internal reports.

Requirements

• Currently enrolled in a Master’s degree program at a Dutch university in Computer Science, Data Science, Biomedical Engineering, or a related field.
• Available for a minimum of 6 months (up to 12 months).
• Proficiency in Python or a similar programming language.
• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and image analysis techniques.
• Familiarity with version control (e.g., Git) and handling large-scale datasets.
• Foundational knowledge of cancer biology and/or immunology, with an interest in integrating imaging and molecular data.
• Familiarity with a collaborative approach within a multidisciplinary team.

Preferred Qualifications, Capabilities, and Skills

• Prior experience with AI applications in drug discovery is an asset.
• Experience working with radiomic data and knowledge of genomics datasets such as those from TCGA and NLST are a plus.
• A proactive mindset with strong analytical and collaborative capabilities and effective communication skills.

General Intern Information

• Internship Duration: 6-12 months
• Start Date: September 1st (or later)
• Location: Utrecht, Netherlands
• Schedule: Hybrid (at least 3 days in the office, 2 days remote per week)

Please note that you must be an actively enrolled student at a Dutch university throughout the internship, and completion of this internship must be a requirement for fulfilling your Master’s degree.

What’s Next?
Help us learn about you by submitting a complete and thoughtful application, which includes your resume 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. Every application matters to us, and we’ll carefully review each submission as quickly as possible to see if your qualifications align with the role. While we’re unable to provide individual updates, rest assured that we’re working diligently to move through the process efficiently. If you move forward in the process, you’ll receive an email invitation to connect with us and dive deeper into this exciting opportunity. The final stage will bring selected candidates meeting directly with our hiring teams, where you’ll have the chance to showcase your potential. We are committed to keeping you informed and will share decisions with all candidates as soon as we are able. We can't wait to see where this journey takes 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!

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.