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Translational Imaging & Multi-Omics Data Science Intern

0-2 years
Not Disclosed
10 Dec. 18, 2025
Job Description
Job Type: Full Time Hybrid Education: B.Sc/M.Sc/M.Pharma/B.Pharma/Life Sciences Skills: Causality Assessment, Clinical SAS Programming, Communication Skills, CPC Certified, GCP guidelines, ICD-10 CM Codes, CPT-Codes, HCPCS Codes, ICD-10 CM, CPT, HCPCS Coding, ICH guidelines, ICSR Case Processing, Interpersonal Skill, Labelling Assessment, MedDRA Coding, Medical Billing, Medical Coding, Medical Terminology, Narrative Writing, Research & Development, Technical Skill, Triage of ICSRs, WHO DD Coding

Translational Imaging & Multi-Omics Data Science Intern | Princeton, NJ

Job ID: R14688
Category: Research & Discovery
Location: Princeton, New Jersey, United States
Job Type: Internship (June – August 2026, Hybrid)


About Genmab

Genmab is a global biotechnology leader focused on improving patient outcomes through innovative antibody therapeutics. With over 25 years of experience, Genmab has developed next-generation antibody platforms, including bispecific T-cell engagers, antibody-drug conjugates, and immune checkpoint modulators.

Headquartered in Copenhagen, Denmark, Genmab operates internationally across North America, Europe, and Asia-Pacific, creating impactful therapies for patients with cancer and other serious diseases.

Learn more at www.genmab.com.


Internship Overview

The Translational Imaging & Multi-Omics Data Science Internship offers a 10-week immersive experience in Genmab’s Translational Data Science team. Interns will gain hands-on exposure to integrating imaging data with multi-omics datasets to discover biomarkers predictive of therapeutic response.

This hybrid internship is based in Princeton, NJ, with 3 days onsite and 2 days remote per week.


Key Responsibilities

Data Integration & Analysis

  • Curate and preprocess histopathology, radiomics, and multi-omics datasets from public and internal sources.

  • Extract quantitative imaging features using deep learning-based models for downstream analysis.

  • Integrate imaging-derived metrics with molecular and clinical data to identify therapeutically relevant subgroups.

Model Development & Optimization

  • Develop graph-based models linking patients, imaging, and molecular features.

  • Apply Graph Neural Networks (GNNs) and related architectures for biomarker discovery and subtype stratification.

  • Utilize cloud computing platforms (e.g., Databricks, AWS) for scalable computation.

Biomarker & Pathway Insights

  • Identify molecular and phenotypic patterns associated with distinct subgroups.

  • Conduct pathway and gene set enrichment analyses to characterize biological differences.

  • Explore potential therapeutic hypotheses using public drug response datasets.

Research Interpretation & Visualization

  • Develop interpretable visualizations and computational frameworks highlighting molecular–morphological relationships.

  • Summarize findings for scientific and strategic discussions via reports, presentations, and figures.


Required Qualifications

  • Current graduate or undergraduate student in Computer Science, Bioinformatics, Data Science, Computational Biology, or related field.

  • Proficiency in Python or R, with experience in machine learning libraries (PyTorch, TensorFlow).

  • Familiarity with image analysis and omics data processing.

  • Strong analytical, problem-solving, and communication skills.

  • Interest in translational and precision medicine research.


Preferred Qualifications

  • Experience with graph-based learning or network biology approaches.

  • Background in digital pathology, image analysis, or biomedical data integration.

  • Familiarity with cloud-based analytical environments (Databricks, AWS).

  • Strong collaborative skills and ability to work in cross-functional teams.


Internship Benefits

  • Hands-on exposure to translational data science and biomarker discovery.

  • Experience with multi-modal data integration, deep learning, and GNNs.

  • Mentorship from experienced computational and translational scientists.

  • Contribute to real-world projects with impact on oncology research and patient care.


About You

  • Passionate about data-driven translational research and precision oncology.

  • Innovative, collaborative, and proactive in fast-paced, scientific environments.

  • Committed to quality, precision, and learning from real-world projects.