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Genmab · 3 days ago

Histopathology Imaging Data Science Intern

Princeton, NJ

Internship

Hybrid

Intern

Start in 2026 Summer

Genmab is an international biotechnology company dedicated to improving the lives of patients through innovative antibody therapeutics. They are seeking a motivated and detail-oriented Histopathology Imaging Data Science Intern to develop AI models for analyzing pathology images and multiomics data, contributing to innovative translational research in cancer treatment.

BiotechnologyHealth CareManufacturingMedical

Culture & Values

No H1B

Responsibilities

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

Qualification

PythonMachine LearningCloud ComputingDigital PathologyMultiomics Data AnalysisImage ProcessingRPyTorchTeam CollaborationCommunication SkillsInitiative