About the Winter School

The Winter School on Scientific Computing and Machine Learning: Principles and Applications aims to equip participants with a deep understanding of computational techniques and data-driven methods for solving complex scientific and engineering problems. Over five days, the program will:
Introduce Core Concepts – Provide foundational knowledge in scientific computing, numerical methods, and machine learning algorithms, emphasizing their relevance in modeling and simulation.
Explore Integration Strategies – Discuss the synergy between machine learning and traditional scientific computing approaches, including physics-informed neural networks (PINNs), surrogate modeling, and data assimilation.
Hands-on Experience – Facilitate interactive sessions, coding labs, and real-world applications to help participants implement computational algorithms and ML models using Python and scientific libraries. This Winter School is designed for graduate students, researchers, and professionals aiming to enhance their computational skills and apply machine learning to real-world scientific challenges

Our Speakers

Learn from the best in the industry with our distinguished speakers who bring years of expertise and innovation to the workshop.

Fees & Registration

Secure your spot for an unforgettable day of learning and networking. Review the registration fees below and register now!

Meet the Organisers