Welcome to the 1^st edition of the International DIADEM Summer School

Artificial Intelligence & Materials Science: Where Innovation Begins

The International DIADEM Summer School is aimed at undergraduate (End of Bachelor, L3), Master’s and PhD students who are eager to explore the synergy between artificial intelligence and materials science. This first edition will take place on the Pierre and Marie Curie Campus of Sorbonne University, offering a one-week immersive training that bridges fundamentals and real-world applications in Material Science.

💼 Format

Designed as a springboard into advanced academic and research careers, this unique school combines:

• Interactive courses on machine learning and its applications to materials,

• Hands-on lab practices and collaborative projects,

• Lectures by internationally renowned researchers,

• A dynamic environment to develop key transferable skills for both academia and industry.

👥 Target audience

Last year of Bachelor or Licence (L3), Master’s and PhD students
In materials science, physics, chemistry, or artificial intelligence.

The International DIADEM School aims to empower a new generation of scientists to tackle tomorrow’s challenges by harnessing AI in the context of materials research. Join us for this first edition and become part of this exciting momentum!

🗣️ Language of Courses

English

Practical details :

The 2025 edition of the International DIADEM Summer School will take place from August 25 to 29, 2025, on the Pierre and Marie Curie Campus of Sorbonne University in Paris, with the support of the Materials Institute of Sorbonne University and University Grenoble Alpes.

This edition focuses on training students and early-stage researchers in computational methods for atomic, molecular, and condensed-phase systems, covering both foundational concepts and cutting-edge techniques, including the integration of artificial intelligence into atomistic simulations.

Program Highlights

Participants will have the opportunity to explore various machine learning approaches applied to materials, both from numerical and experimental perspectives:

• Basic machine learning techniques and their application in real-world case studies

• Advanced techniques: materials discovery, generative methods, PiNN

• Atomistic approaches: standard methods and the construction of computational interatomic potentials

• Computational tools: code containerization, Python Jupyter Notebooks

• Hands-on, where students will apply these methods to concrete scientific problems

The program is designed to provide students with a solid theoretical foundation, while also developing their critical decision-making abilities in choosing the right methods for specific scientific challenges.

A Unique School in the Heart of Paris

The school benefits from the exceptional setting of central Paris and the strong local presence of experienced and early-career researchers, all experts in their respective fields. Participants will engage in both structured learning and collaborative work, within an international and multidisciplinary environment.