Lead the creative research, architecture design, and training of Biological Foundation Models (BioFMs), on massive-scale genomic, transcriptomic, and single-cell datasets.
Collaborate closely with computational biologists and drug developers to integrate deep biological priors directly into model architectures and training objectives, ensuring our BioFMs capture fundamental and scientifically meaningful representations.
Lead the research and development of novel deep learning architectures, training paradigms (e.g., supervised, self-supervised, generative, multi-modal), and algorithms tailored for large-scale biological sequence data and related modalities.
Partner with world-class computational biologists to integrate domain expertise, define scienti...
