Postdoctoral Research Associate in Multimodal Foundation Models for Healthcare (Two Posts)
Core
Building next-generation multimodal foundation models that learn from diverse health data including biosignals, electronic health records, imaging, and biomedical knowledge to advance clinical and biomedical applications.
Role type
Postdoctoral Research Associate (PhD level)
Builds
Unified multimodal foundation models, generative health AI, and knowledge-graph-enhanced systems for healthcare.
Domain
Healthcare AI, Machine Learning, Biomedical Engineering
Deliverable
production ML models
Required skills
Multimodal learning, self-supervised learning, representation learning, biosignal or time-series modelling, large-scale or generative foundation models, knowledge graphs, graph learning, retrieval-augmented methods, machine learning theory, distributed training
Preferred skills
Experience with healthcare or biomedical data
Technologies
National AI compute infrastructure, GPU clusters
Responsibilities
Define scientific direction for multimodal foundation models, develop scalable generative health AI architectures, research theory of unified multimodal models
Seniority
Early-career researcher (Postdoc)
