Machine learning techniques are becoming ubiquitous in scientific and engineering applications. For mathematicians, this presents both challenges and opportunities in understanding and integrating new tools and methods alongside — or instead of — classical techniques. Key open questions regarding the stability, reliability, and efficiency of machine learning approaches can be addressed through mathematics, particularly numerical analysis. A deeper mathematical understanding of machine learning techniques, along with collaboration between developers, analysts, and users, holds great potential for scientific progress and societal impact.
Autumn School on Scientific Machine Learning and Numerical Methods
📅 Dates: 27–31 October 2025
📍 Location: Turing Hall, CWI, Science Park 125, Amsterdam, Netherlands
This school is designed for advanced Master’s students and early-stage PhD researchers, providing a preparatory PhD-level introduction to the subject.
For more information and registration, visit the 2025 Autumn School programme.
Workshop on industrial applications of numerical analysis and machine learning
📅 Dates: 1–3 December 2025
📍 Location: Euler, CWI, Science Park 125, Amsterdam, Netherlands.
We welcome contributions and participation from researchers and professionals in related fields.
Further details will follow.
