Senior Applied Research Scientist, Multimodal Foundation Models – Healthcare - CA, Santa Clara, United States

Originally posted 13 August 2026 by the employer.

About the role

This role focuses on advancing longitudinal multimodal foundation models for healthcare by exploring models that learn from longitudinal medical imaging, electronic health records, laboratory measurements, genomics, medications, diagnoses, and clinical outcomes.

What you'll do

• Conduct research on longitudinal multimodal foundation models that learn from heterogeneous healthcare data.
• Develop novel foundation model architectures and training strategies for disease progression modeling, treatment response prediction, temporal reasoning, and multimodal generative modeling.
• Build large-scale datasets, benchmarks, and open-source foundation models that advance healthcare AI.
• Collaborate with researchers across Healthcare AI, BioNeMo, and other NVIDIA teams to develop multimodal biological foundation models spanning imaging and molecular data.
• Publish research in AI and healthcare venues, contribute to open-source software and models, and help define the direction of healthcare foundation models.

What you'll need

• PhD in Computer Science, Machine Learning, Biomedical Engineering, Computational Biology, Electrical Engineering, or a related quantitative field (or equivalent experience).
• 8+ years of relevant industry experience focusing on medical AI research.
• Research experience developing multimodal foundation models that integrate heterogeneous clinical or biological data, such as medical imaging, electronic health records (EHR), laboratory measurements, genomics, pathology, medications, diagnoses, and clinical outcomes, with an emphasis on longitudinal modeling, temporal reasoning, or disease progression prediction.
• Experience developing and training large-scale foundation models using deep learning frameworks such as PyTorch.
• Strong software engineering and experimental skills, including building scalable, reproducible research pipelines.

Skills: multimodal foundation models, healthcare AI, deep learning frameworks, PyTorch, longitudinal modeling, temporal reasoning