AI-Driven Radiomics and Multimodal Biomarker Discovery Intern

Genmab is an international biotechnology company dedicated to improving the lives of patients through innovative antibody therapeutics. The AI-Driven Radiomics and Multimodal Biomarker Discovery Intern will work on developing deep learning frameworks for biomarker discovery in cancer treatment, integrating clinical imaging with genomic profiles. Responsibilities Deep Learning Architecture Development: Design, train, and optimize advanced CNN-based and hybrid architectures (e.g., 3D CNNs, Vision Transformers, CNN -Transformer hybrids) to extract biologically meaningful radiomic representations Multimodal Data Integration: Develop deep fusion models that combine imaging, molecular, and clinical data through cross-attention, late fusion, or graph-based techniques to enhance biomarker prediction and interpretability Software Engineering & Reproducibility: Write clean, modular, and well-documented code following modern software engineering best practices Feature Interpretation & Biomarker Discovery: Correlate learned features with genetic mutations (e.g., KRAS, EGFR, TP53), immune profiles, and clinical outcomes to identify interpretable and actionable biomarkers Model Validation & Generalization: Conduct rigorous cross-validation, hyperparameter optimization, and external dataset validation to assess model robustness and reproducibility Collaboration & Communication: Work closely with computational biologists, bioinformaticians, and clinicians. Present progress and findings in internal seminars and contribute to internal reports and potential publications Skills Currently pursuing a PhD or advanced Master's degree in Computer Science, Data Science, Biomedical Engineering, Computational Biology, or a related quantitative discipline Proficiency in Python and deep learning frameworks such as PyTorch Demonstrated experience developing CNNs, transformers, or multimodal architectures for medical imaging, omics, or related AI applications Experience with data management and distributed training frameworks (e.g., Weights & Biases) Familiarity with radiomics extraction libraries (e.g., PyRadiomics, MONAI) Knowledge of model interpretability tools (Grad-CAM, SHAP, feature attribution) and evaluation metrics for biomedical data Soft Skills: Analytical mindset, collaborative spirit, strong organizational skills, and proactive attitude Strong understanding of or interest in cancer biology Company Overview Genmab is a biotechnology company focused on developing fully human antibody therapeutics for the potential treatment of cancer. It was founded in 1999, and is headquartered in Copenhagen, Hovedstaden, DNK, with a workforce of 1001-5000 employees. Its website is