Intern, Translational Data Science (Project: Multiscale AI for Tissue Representation and Biomarker Discovery)

Genmab; Utrecht; On-site; EUR 7,600 - 9,100; Full time

Benefits offered by this job

Pension

Health insurance and wellness benefits

Paid time off

Employee support programs

Job summary

Genmab is seeking an motivated intern to join the Translational Data Science team in Utrecht. You will work on multimodal models that combine clinical imaging with molecular data and develop an interpretable tissue-token codebook that links radiology, pathology, and molecular programs.

Public and commercial data will be used to advance biomarker discovery and biologic hypothesis generation. You will collaborate with computational biologists, pathologists, imaging scientists, and clinicians,

Qualifications

• Enrolled in a Dutch university Master’s program in Computer Science, AI, or related quantitative field.
• Internship must be a mandatory component of your degree program for graduation; not for graduates or extracurricular internships.
• Available for a minimum of 6 months.
• Proficiency in Python and deep learning frameworks such as PyTorch.
• Experience developing CNNs, transformers, self-supervised models, or multimodal architectures for medical imaging, digital pathology, omics, or related applications.
• Familiarity with medical imaging libraries/workflows (MONAI, PyRadiomics, OpenSlide) is desirable.

Responsibilities

• Design and validate multimodal models that integrate imaging with molecular and clinical data to identify meaningful biomarkers.
• Learn discrete tissue tokens across scales to create an interpretable biologic dictionary.
• Integrate data from HEST-1k, TCGA, CPTAC-linked cohorts, radiogenomic imaging cohorts, and internal resources.
• Connect learned representations with genetic alterations, immune profiles, pathway activity, and treatment outcomes.
• Write clean, modular, reproducible code and conduct cross-validation and external validation.
• Collaborate with computational biologists, bioinformaticians, pathologists, imaging scientists, and clinicians and present progress internally.

Skills

Python

PyTorch

Deep learning

CNNs

Transformers

Multimodal architectures

Medical imaging

Experiment tracking

Weights & Biases

Data management

Education

Master's degree in CS/AI

Tools

MONAI

PyRadiomics

OpenSlide

Job description

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 and cancer immunology, looking to make a meaningful impact in the field of antibody therapeutics? Do you want to gain exposure to the strategic design of innovative antibody therapeutics? Keep reading!

We are looking for a highly motivated intern to join Genmab’s Translational Data Science team. You will work on two connected directions: multimodal models that integrate clinical imaging with molecular and genomic profiles, and an interpretable tissue-token codebook that translates morphology across radiology, whole-slide pathology, and molecular programs. The work will use public and commercial data to advance biomarker discovery and biologic hypothesis generation.

Responsibilities

• Pillar 1 - Multimodal Biomarker Discovery: Design and validate models that integrate CT, MRI, or PET radiomics with molecular, genomic, and clinical data to identify meaningful, actionable biomarkers.
• Pillar 2 - Tissue Token Codebook Across Scales: Learn discrete tissue tokens in a shared semantic space spanning CT habitats, whole-slide imaging patterns, and molecular programs. Ground tokens in imaging, pathology, and omics evidence to create an interpretable biologic dictionary rather than a black-box embedding.
• Data Integration & Method Development: Use HEST-1k, TCGA, CPTAC-linked cohorts, radiogenomic imaging cohorts, and relevant internal resources. Explore CNNs, vision transformers, self-supervised learning, cross-attention, graph methods, and discrete representation learning.
• Feature Interpretation & Hypothesis Generation: Connect learned representations with genetic alterations, immune profiles, pathway activity, morphology, treatment response, and outcomes to support biomarker discovery and cross-study reuse.
• Model Validation, Generalization & Reproducibility: Conduct cross-validation, ablation studies, and external validation. Write clean, modular, well-documented code following reproducible research practices.
• Collaboration & Communication: Work closely with computational biologists, bioinformaticians, pathologists, imaging scientists, and clinicians. Present progress and findings in internal seminars and contribute to internal reports and potential publications.

Requirements

• Currently enrolled in a Master’s degree program at a Dutch university in Computer Science, Artifical Intelligence or a related quantitative discipline.
• 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.
• Proficiency in Python and deep learning frameworks such as PyTorch.
• Experience developing CNNs, transformers, self-supervised models, or multimodal architectures for medical imaging, digital pathology, omics, or related applications.
• Experience with data management, experiment tracking, and scalable training workflows (e.g., Weights & Biases).
• Familiarity with medical imaging or pathology libraries and workflows (e.g., MONAI, PyRadiomics, OpenSlide) is desirable.
• Knowledge of representation learning, interpretability, clustering or vector quantization, and biomedical evaluation methods.
• Strong understanding of or interest in cancer biology, pathology, radiology, or spatial omics is highly desirable.
• Soft Skills: Analytical mindset, collaborative spirit, strong organizational skills, clear communication, and a proactive attitude.

General Information

• Internship duration: 6-9 months.
• Start date: February 1st 2027.
• Location: Utrecht, Netherlands

The proposed gross annual/monthly base salary range for this position, in the primary location, based on a full time schedule is:

EUR750,00---750,00

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-gen antibody technology platforms and harnessed translational, quantitative and data sciences, resulting in a proprietary pipeline including bispecific T-cell engagers, antibody-drug conjugates, next-géneration 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.