The French Research Network "GDR IAMAT" organizes a Spring school in the beautiful location of Roscoff, France, focusing on machine learning in computational materials science. There will be a maximum of 45 attendants, with priority given to non-permanent researchers, and poster sessions.

The school itself will be organized on five days, from Monday 17^th of April 2023 early morning to Friday 21^st of April at noon, with, each day, two morning lectures followed, in the afternoon, by hands-on computer tutorials, which will allow participants to become operationally familiar with the machine-learning approached described and explained in the corresponding morning lectures.

The second part of two afternoons will be dedicated to poster sessions, which will be introduced orally via flash-presentations.

Confirmed speakers:

• Aurélien Decelle – Statistical methods for machine learning
• Jean-Luc Parouty – Machine learning with deep neural networks
• Jörg Behler – Neural network potentials for atomistic simulations
• Filippo Vicentini – Neural networks quantum states
• Arthur France-Lanord – Dynamics and transformations at the atomic scale using ML
• Joao Paulo Almeida de Mendonca – Beyond DFT: learning new functionals
• Ludovic Goudenège – Machine learning in phase-field approaches
• Cosmin Marinica – Surrogate models
• Pauline Besserve – Beyond the ground state: accelerating DMFT with quantum computers

For more details and pre-inscription procedure (before the 31st of January), please visit https://gdr-iamat.sciencesconf.org/?forward-action=index&forward-controller=index&lang=en