Translational Imaging & Multi-Omics Data Science Intern

Summary: Genmab is an international biotechnology company dedicated to improving the lives of patients through innovative antibody therapeutics. They are seeking a motivated intern to join the Translational Data Science team, focusing on integrating imaging features with multi-omics data to uncover therapeutic opportunities. Responsibilities: - Process and curate histopathology and/or radiomics image datasets and multi-omics profiles from public and internal sources - Extract quantitative image features using deep learning-based models (e.g., foundation models for whole-slide analysis) - Integrate imaging-derived metrics with molecular and clinical data for downstream analytics - Build and evaluate graph-based models linking patients and molecular/imaging features - Apply GNNs and related architectures to explore subtype stratification and biomarker discovery - Utilize cloud computing platforms (e.g., Databricks, AWS) for scalable computation - 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 and perturbation datasets - Develop interpretable visual and computational frameworks that highlight molecular–morphological relationships - Summarize findings for scientific and strategic discussions through figures, reports, and presentations Required Qualifications: - Current graduate or undergraduate student in Computer Science, Bioinformatics, Data Science, Computational Biology, or related field - Proficiency in Python or R; experience with machine learning libraries (e.g., PyTorch, TensorFlow) - Familiarity with image analysis and omics data processing - Strong analytical and problem-solving skills, with attention to detail - 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) - Excellent communication skills and ability to work in a collaborative team Required Skills: Python, R, Machine learning, PyTorch, TensorFlow, Image analysis, Omics data processing, Graph neural networks, Graph-based learning, Network biology, Digital pathology, Biomedical data integration, Cloud computing platforms, Databricks, AWS, Analytical skills