Teaching

Courses and seminars offered by the group.

• Winter 2026/27
  Master's Lab Course

  AI for Science is the term loosely used for applying modern artificial intelligence methods to accelerate discovery and deepen understanding in the natural and applied sciences. It uses generative models to suggest new ideas, neural networks to replace slow simulations, and Bayesian optimizers to guide experiments as they progress. Together, these tools greatly reduce the time to advance science and make discoveries. Initial breakthroughs highlight the magnitude of this paradigm shift: AlphaFold 3 now predicts full protein–nucleic acid–ligand complexes with near-atomic accuracy, condensing months of wet-lab crystallography into minutes of GPU time. At the laboratory bench, agentic platforms are beginning to knit simulations, robotic synthesizers and language‑model planning into a continuous, self‑refining loop of experimentation. In this lab, you will study these methods in depth by implementing some of them and running different analyses on them. You will evaluate your learnings by presenting the method for the class, giving a short demonstration and delivering a final report.

  9CP

• Master's Lab Course
  Spring 2026 · 9CP
• Computation and Fabrication
  Spring 2021 · 6 CP
• Seminar on Computational Design and Manufacturing
  Winter 2019/20 · 7(8) CP
• Seminar on Computational Fabrication
  Winter 2018/19 · 7(8) CP