Postdoctoral Appointee - AI for Biomedical Discovery

Argonne National Laboratory seeks two postdoctoral researchers for the Forge project, which develops secure, scalable, continuously learning multimodal AI for biomedical discovery that can learn across distributed data environments without centralising sensitive data. The work spans federated learning, foundation-model adaptation, multimodal biomedical AI across clinical, imaging, omics, text and experimental data, privacy-preserving machine learning, continual learning and agentic AI for orchestrating federated training, with deployment on cloud, secure enclaves, trusted research environments and leadership computing platforms.

Postdocs contribute to open-source software and publish and present their research. The expected hiring range is $72,879–$121,465.

Ph.D. (within the last 0–5 years) in computer science, data science, biomedical informatics, computational biology, bioengineering, applied mathematics, electrical engineering or a related field; strong Python skills and experience building research or production-quality ML software with PyTorch, TensorFlow, JAX or similar; knowledge of federated or distributed learning, privacy-preserving AI, foundation models, multimodal or continual learning; experience with large, complex or multimodal datasets. Preferred: federated learning frameworks (APPFL, Flower, FedML, NVIDIA FLARE), multimodal biomedical data, foundation-model fine-tuning, agentic AI and privacy techniques such as differential privacy or secure aggregation.