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Training Workshop: An Introduction to Diffusion Models in Generative AI

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About this event

What to expect

This full-day intensive training workshop offers researchers and postgraduate students a comprehensive introduction to diffusion models — the powerful technology behind AI image generators like Dall-E, Midjourney, and Sora, as well as breakthrough research tools like AlphaFold. Hosted by the University of Cambridge's Accelerate Programme, this event provides both theoretical understanding and practical insights into how these models are transforming scientific research.

What You'll Learn

The workshop takes a conceptual, high-level approach to understanding how generative AI and diffusion models work under the hood. While there's no live coding during the session, participants will receive code samples to experiment with afterward. By the end of the day, you'll have a firm grasp of the mathematical and algorithmic principles that make diffusion models so powerful across diverse applications.

The curriculum explores real-world research applications across multiple domains:

  • Drug discovery — accelerating molecular design and compound screening
  • Weather forecasting — improving prediction accuracy through generative modeling
  • Synthetic speech — creating realistic audio outputs
  • Medical imaging — enhancing diagnostic capabilities and image reconstruction

Speaker Sessions & Networking

A highlight of the workshop is hearing from Cambridge researchers who are already deploying diffusion models in their own work. These short talks provide practical perspectives on implementation challenges, research outcomes, and lessons learned from real projects. The networking lunch offers an excellent opportunity to connect with peers working on similar problems and to discuss potential collaborations.

Who Should Attend

This workshop is open to all postgraduate students and research staff at the University of Cambridge. Whether you're exploring generative AI for the first time or looking to understand how diffusion models might enhance your existing research, the content is designed to be accessible while maintaining technical depth. No prior experience with diffusion models is required, though familiarity with basic machine learning concepts will be helpful.

The event takes place in Cambridge and includes lunch and refreshment breaks, creating space for informal discussions and knowledge sharing among the research community.

[Register for this workshop](https://training.ca

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