The GDR IAMAT organizes a Spring school in the beautiful location of Roscoff, 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 – Learning new DFT functionals
• Ludovic Goudenège – Machine learning in phase-field approaches
• Cosmin Marinica – Overview of surrogate machine learning models for materials science
• Pauline Besserve – Beyond the ground state: accelerating DMFT with quantum computers

The normal fee of 480 euros includes housing (from Sunday 15^th of April evening to Friday morning) and meals (from Monday morning to Friday lunch). Attendance is free for participants employed by CNRS, and there will be a discount for participants employed by CEA (depending on the total number of CEA attendees).

To participate, please fill in the registration form including a few lines about your work and motivation, before the 31^st of January. Please specify in case you are directly employed by CNRS or by CEA. Applicants will be notified around mid-February whether they are selected or not.

Pour garder le contact avec notre goupe de recherche, nous vous proposons de nous rejoindre sur notre liste de diffusion (site : https://listes.services.cnrs.fr/wws/info/gdr_iamat-inscrits) et de nous suivre sur notre site:

https://iamat.cnrs.fr/

Under the auspices of the INP and the INC (National Instituts of Physics and of Chemistry of CNRS), the research group GDR IAMAT (Artificial Intelligence in Materials Science) has officially begun to operate on January 1st, 2022. We suggest you to join us on our mailing list via the home page: https://listes.services.cnrs.fr/wws/info/gdr_iamat-inscrits.

The mission and main objective of the research group GDR IAMAT is to bring together the many teams and different communities interested in artificial intelligence approaches in theoretical and experimental materials science. The scientific topics cover the continuum from AI developments to concrete applications in materials science. The key goals are to promote educational exchanges between communities, particularly through transverse actions, and to foster new inspirations and collaborations.

The GdR IAMAT is organized following a matrix structure. The “lines” correspond to the scientific challenges identified. The “columns” correspond to AI/ML general classes of algorithms and methods, which are transversal to the needs of the scientific challenges.

Director

A. Marco Saitta (IMPMC - Paris)

Deputy directors

Magali Benoit (CEMES - Toulouse)

Silke Biermann (CPhT - Saclay)

Jean-Claude Crivello (ICMPE - Thiais)

Scientific board

Alexandre Boulle (IRCER - Limoges)

Alexis Deschamps (SIMAP - Grenoble)

Guilhem Dezanneau (SPMS - Saclay)

Gabriel Stoltz (CERMICS - Marne-la-Vallée)

Franck Tancret (IMN - Nantes)

Ambroise Van Roekeghem (LITEN - Grenoble)

Helena Zapolsky (GPM - Rouen)