Hosted by Computing Sciences at Berkeley Lab, the 2025 Deep Learning for Science (DL4SCI) Summer School is a five-day immersive program bringing together researchers and engineers to explore the latest advances in deep learning and generative AI (GenAI). 

The school will feature in-depth lectures, research talks, and hands-on tutorials on state-of-the-art techniques, including transformers, large language models, diffusion models, flow matching, and generative adversarial networks, as well as practical sessions on best practices for running deep learning at scale on high-performance computing systems. Theory will be covered, but the program places an emphasis on practical application. Local and international AI experts will lead interactive labs and offer state-of-the-art code and content. Attendees will gain a strong understanding of what GenAI is, the types of problems it excels at, and how to choose, build, train, and deploy GenAI models for scientific applications.

The Summer School will also facilitate networking and collaboration through breakout sessions, group activities, and optional poster sessions. These forums will allow participants to engage directly with instructors and peers, fostering vibrant discussions on how current research trends and new learning algorithms can be leveraged in scientific domains. By the end of the program, attendees will be equipped with the tools and expertise necessary to implement and scale modern AI solutions in their research.