Histopathology Imaging Data Science Intern Job at Genmab, Princeton, NJ

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  • Genmab
  • Princeton, NJ

Job Description

At Genmab we are dedicated to building extranotordinary 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!

Job Title

Histopathology Imaging Data Science Intern

Why Genmab

Our internship program provides interns with hands-on experience and relevant projects that directly align with our companys goals. Additionally we believe our program provides a valuable opportunity to learn thrive and build a strong network. We encourage you to review our website to learn why were always looking for smart purpose-led candidates to play a role in our bold extranotordinary future.

Job Overview

We are looking for a motivated and detail-oriented Digital Pathology Intern to join our team for a summer internship. This role will focus on developing AI models to analyze H&E and IHC images and multiomics data (such as RNAseq and DNA mutations) to characterize the tumor microenvironment and uncover biomarkers linked to disease biology and treatment efficacy. The intern will collaborate with our translational data science team and other stakeholders to contribute to innovative translational research in cancer treatment.

What Youll Do

  • Data ingestion & Analysis

    • Develop or utilize pathology-specific foundation models e.g. CTransPath PLIP and BiomedParse to process and analyze large image datasets

    • Perform integrative analysis of pathology images with multiomics datasets (e.g. RNAseq DNA mutations).

    • Integrate and preprocess datasets and software packages from diverse sources to ensure compatibility with AI tools.

    • Conduct computation in a GPU-enabled environment on cloud platforms.

  • Model Development & Optimization

    • Assist in fine-tuning and optimizing AI models for tasks such as image segmentation and classification using python/R.

    • Add new functions to the current pipeline of imaging data analysis.

    • Document and present model performance metrics to the team.

  • Biomarker Discovery

    • Apply deep learning/machine learning techniques to predict mutations and/or protein expression and identify potential biomarkers associated with tumor characteristics and treatment outcomes.

    • Work with mentors and other researchers to validate findings and assess their relevance to cancer biology and therapeutic strategies.

  • AI Model interpretability

    • Develop interactive tools enabling pathologists to review whole slide images (WSIs) and evaluate integrated AI predictions on the tumor microenvironment (TME). The tools will leverage diverse vision-language foundation models to enhance model validation and interpretability and bring insights into cancer biology.

  • Research & Reporting

    • Conduct literature reviews to keep abreast of the latest developments in deep learning digital pathology and multiomics integration.

    • Prepare reports and presentations to share findings with both technical and non-technical audiences.

Required Qualifications Capabilities and Skills

  • Currently enrolled in a degree program in Computer Science Bioinformatics Data Science or a related field.

  • Proficiency in programming languages such as Python or R.

  • Experience with machine learning frameworks (e.g. PyTorch) and data analysis tools.

  • Familiarity with image processing and analysis techniques.

  • Experience with cloud computing platforms e.g. AWS DataBricks.

  • Ability to collaborate effectively in a team setting.

  • Demonstration of initiative a proactive attitude and eagerness to learn in a fast-paced environment.

Preferred Qualifications Capabilities and Skills

  • Prior experience with digital pathology or multiomics data analysis.

  • Basic understanding of cancer biology or oncology research.

  • Excellent written and verbal communication skills.

  • Familiarity with AI coding/agent tools (e.g. Cursor).

General Intern Information Date/Location/Schedule

Internships will take place June August 2026. This role will be based in Princeton NJ and operate on a required hybrid schedule 3 days in the office and 2 days remote per week.

Whats next

Help us learn about you by submitting a complete and thoughtful application which includes your resume. Your application and resume are a way for us to initially get to know you so its important to complete all relevant questions to ensure we have as much information about you as possible.

Every application matters to us and well carefully review each submission as quickly as possible to see if your qualifications align with the role. While were unable to provide individual updates rest assured that were working diligently to move through the process efficiently.

If you move forward in the process youll 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 youll 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 cant wait to see where this journey takes you.

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 youre 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 Genmabs 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 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 ().

Required Experience:

Intern

Job Tags

Full time, Summer internship, Work at office, Remote work, 2 days per week,

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