AI for Science Center
The AI for Science Center trains students to design and build AI methods that accelerate scientific discovery on their own. Coursework centers on real scientific problems - protein folding, materials design, weather and climate modeling, and mathematical reasoning - and requires students to construct and validate scientific foundation models, physics-informed and equivariant neural networks, and simulation-based inference pipelines. Students also join cross-division AI4Science projects, learning to integrate data and requirements across scientific disciplines. Graduates leave able to architect an AI pipeline for a novel scientific problem from the ground up.
Field-based Curriculum · 16
This department's curriculum is built directly on the GeoVerse Lab research fields its professors hold — click a field to see how it is taught.
