Intern, Discovery Data Science (Project: Spatial Transcriptomics for Antibody Based Drug Discovery and Development in Solid Tumors)

Genmab
Genmab logo
Location
Utrecht
Job Type
Full-time
Posted
October 20, 2026

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!



Interested in more than one (Data Science) internship?


We are posting several projects within our Utrecht Genmab site, each with its own research focus, recruitment team, and selection process. Please take time to explore the available projects andapply to a maximum of twothat best match your interests and skills.


If you apply to two, includethe project titles in order of preference in both motivation letters, with a brief explanation of your interest in each. This helps our teams understand your preferences throughout the separate selection processes!


The Role


How can the location of a cell within a tumor help us discover new therapeutic targets? Join Genmab as a Data Science intern and explore how spatial transcriptomics can support the discovery of antibody-based treatments.

Bulk and single-cell RNA sequencing help us understand which cells are present and which genes they express. Spatial transcriptomics takes this further by showing where those cells are located within the tissue. This gives us a richer picture of the tumor microenvironment and new opportunities to investigate potential therapeutic targets.


Working closely with our Target and Product Discovery teams, you will analyze spatial transcriptomics data from solid tumors and develop methods to turn complex datasets into meaningful biological insights. You will explore questions such as: What makes a target’s expression specific to a tumor? How might its location influence accessibility to an antibody-based therapeutic? And what can spatial data tell us that bulk and single-cell approaches cannot?


You will gain hands-on experience in analytical method development, data analysis, project planning, and presenting your findings to scientific colleagues. With the research questions still taking shape, there is room to bring your own ideas and help define the direction of your project. This is an opportunity to develop your data science skills while contributing to real questions in early drug discovery!


Responsibilities


  • Perform advanced analysis of spatial transcriptomics datasets from solid tumors.
  • Develop and benchmark computational approaches for using spatial data in tumor-specific target discovery, including integrated use of bulk and single-cell RNA sequencing data for tatget discovery.
  • Translate findings into insights to inform antibody product discovery.
  • Communicate findings effectively through reports and presentations.

Requirements


  • Enrolled in a Master's program in Molecular Biology, Biomedical Sciences, Bioinformatics, or a related field at a University in the Netherlands.
  • 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.
  • Experience with Python and/or R programming.
  • You have a foundational knowledge of cancer biology and/or immunology.
  • You have experience in, or a strong interest in learning, spatial transcriptomics data analysis and antibody drug discovery.
  • Familiarity with transcriptomics data in general (bulk and/or single-cell RNA sequencing) is an advantage.
  • You are comfortable working on questions where the methodology is not yet established and are motivated to help develop it.
  • You enjoy working collaboratively in a multidisciplinary team.
  • Excellent communication and collaboration skills in English.
  • Previous programmin

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!



Interested in more than one (Data Science) internship?


We are posting several projects within our Utrecht Genmab site, each with its own research focus, recruitment team, and selection process. Please take time to explore the available projects andapply to a maximum of twothat best match your interests and skills.


If you apply to two, includethe project titles in order of preference in both motivation letters, with a brief explanation of your interest in each. This helps our teams understand your preferences throughout the separate selection processes!


The Role


How can the location of a cell within a tumor help us discover new therapeutic targets? Join Genmab as a Data Science intern and explore how spatial transcriptomics can support the discovery of antibody-based treatments.

Bulk and single-cell RNA sequencing help us understand which cells are present and which genes they express. Spatial transcriptomics takes this further by showing where those cells are located within the tissue. This gives us a richer picture of the tumor microenvironment and new opportunities to investigate potential therapeutic targets.


Working closely with our Target and Product Discovery teams, you will analyze spatial transcriptomics data from solid tumors and develop methods to turn complex datasets into meaningful biological insights. You will explore questions such as: What makes a target’s expression specific to a tumor? How might its location influence accessibility to an antibody-based therapeutic? And what can spatial data tell us that bulk and single-cell approaches cannot?


You will gain hands-on experience in analytical method development, data analysis, project planning, and presenting your findings to scientific colleagues. With the research questions still taking shape, there is room to bring your own ideas and help define the direction of your project. This is an opportunity to develop your data science skills while contributing to real questions in early drug discovery!


Responsibilities


  • Perform advanced analysis of spatial transcriptomics datasets from solid tumors.
  • Develop and benchmark computational approaches for using spatial data in tumor-specific target discovery, including integrated use of bulk and single-cell RNA sequencing data for tatget discovery.
  • Translate findings into insights to inform antibody product discovery.
  • Communicate findings effectively through reports and presentations.

Requirements


  • Enrolled in a Master's program in Molecular Biology, Biomedical Sciences, Bioinformatics, or a related field at a University in the Netherlands.
  • 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.
  • Experience with Python and/or R programming.
  • You have a foundational knowledge of cancer biology and/or immunology.
  • You have experience in, or a strong interest in learning, spatial transcriptomics data analysis and antibody drug discovery.
  • Familiarity with transcriptomics data in general (bulk and/or single-cell RNA sequencing) is an advantage.
  • You are comfortable working on questions where the methodology is not yet established and are motivated to help develop it.
  • You enjoy working collaboratively in a multidisciplinary team.
  • Excellent communication and collaboration skills in English.
  • Previous programming experience, ideally with the development of your own package.

Preferred Qualifications, Capabilities, and Skills


  • Hands-on experience with single cell and spatial transcriptomics technologies and their analysis ecosystems.
  • Knowledge of ML / AI techniques applied to target discovery and spatial or single-cell data analysis.
  • Experience with biomedical datasets, including image-based or spatially resolved data.
  • Familiarity with immuno-oncology and solid tumor biology.
  • Previous industry experience or internship in a related field.

General Internship Information


  • Internship duration: 7-10 months (a minimum of 7 months is required due to the complexity of the project; please only apply if you can commit to this duration).
  • Start date:1 Feb/March 2027 (fixed start dates aligned with our internship cohorts, so you can join fellow students for onboarding and make the most of the shared learning activities throughout your internship).
  • Location:Utrecht, Netherlands
  • Working arrangement:Full-time, hybrid, with three days onsite and two days working remotely.


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-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 onLinkedInandX.


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 websiteJob 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.

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Frequently Asked Questions

Where is this internship located, and what is the work arrangement?
The position is based in Utrecht, Netherlands. It features a full-time, hybrid working arrangement requiring three days on-site and two days working remotely.
What qualifications and requirements are required for this role?
You must be enrolled in a Master's program in Molecular Biology, Biomedical Sciences, Bioinformatics, or a related field at a Dutch university. The internship must be a mandatory graduation requirement. You need Python and/or R programming experience, foundational cancer biology/immunology knowledge, strong English skills, and ability to commit for 7-10 months.
What are the main responsibilities of the intern?
You will perform advanced analysis of spatial transcriptomics datasets from solid tumors, develop and benchmark computational approaches using spatial and RNA sequencing data for target discovery, translate findings into target insights for antibody products, and communicate your results through reports and presentations.
What is the compensation for this internship?
The proposed gross monthly base salary range for this full-time position in Utrecht is EUR 750,00 - 750,00. The position is also eligible for additional compensation forms like discretionary bonuses and long-term incentives.
What benefits does Genmab offer for this role?
Genmab provides benefits supporting physical, financial, social, and emotional well-being, including paid time off, health insurance and wellness benefits, a pension, and employee support programs.
How do I apply if I am interested in multiple data science projects?
You may apply to a maximum of two projects. If applying to two, list both project titles in order of preference in both of your motivation letters, alongside a brief explanation of your interest in each.

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Job Information

Source: manual
AI Relevance: 95/100 (Highly relevant)
Remote Type: onsite
Skills & Tags:
genmab bioinformatics single-cell drug discovery data science immunology oncology transcriptomics

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