Postdoctoral Scientist – Multimodal Representation Learning for Predictive Biology

Role: Postdoctoral Scientist in Data Analytics & Computational Sciences within Johnson & Johnson's Innovative Medicine division, focusing on multimodal representation learning for predictive biology. Responsibilities: develop AI/ML models for drug discovery using heterogeneous biological data (imaging microscopy, transcriptomics, proteomics), analyze cellular heterogeneity, collaborate across teams to translate models into actionable insights, and publish research findings. Requirements: Ph.D. in Electrical Engineering, Biomedical Engineering, Computer Science, or related; recent completion or within 6 months; expertise in AI/ML for biological applications, deep learning architectures (Transformers, CNNs), and experience with multimodal biological data; proficiency in Python, PyTorch or TensorFlow. Preferred: strong publication record, experience in foundation models, multi-omics, and advanced imaging techniques. HighValue: focus on AI/ML for biological data, multimodal modeling, drug discovery, and cellular heterogeneity analysis. WorkSetup: locations include Cambridge, MA (preferred), Spring House, PA, Beerse, Belgium, or Madrid, Spain; no remote option.