RESOURCES

Compute, Core Facilities & Funding at Discovery AI 

At Duke University, we provide a powerful infrastructure for AI-driven biology: our teams operate on a cluster of ~100 NVIDIA H200 GPUs, enabling large-scale model training, protein design workflows and deep computational biology pipelines. In parallel, Duke’s high-performance computing ecosystem (including the Duke Compute Cluster) supports massive multi-core jobs, data-intensive analytics and Jupyter/RStudio interactive workflows.

We also invest in the next generation of AI-bio scientists through our Discovery AI Scholars program, which provides funding, mentorship and access to infrastructure for postdocs working at the interface of computation and the life sciences.

Three colorful GPUs with their packaging cleanly removed laying on a white surface. Credit: Fritzchens Fritz

Core Networks & Resources

In addition to compute, our biological research is supported by Duke’s world-class core facility networks. These include (but are not limited to):

Discovery AI s also building a dedicated protein/biologic-design & structure core, purpose-built for model-driven molecule engineering, structural analysis and integration with AI pipelines. Together, these resources enable seamless workflows from algorithm development → modelling → design → biological generation → analysis.

Whether your focus is deep learning, computational biology, synthetic biology, structural modelling or large-scale data generation, you’ll find in this ecosystem the tools, infrastructure and collaborative community to bring bold ideas to life.

Additional Resources & Partnerships

Image displays logos of different Duke University AI programs, centers, and initiatives.