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The innovative e-learning platform, Lhumos, has ventured into the realm of material sciences with the aim of facilitating knowledge sharing and capacity building within the material sciences community and beyond.

Given the increasing demand for coding skills in the technology industry, there is a crucial need to enhance code usage and provide training on various methods in High-Performance Computing (HPC) environments.

Developed with the support of MaX, CECAM, MARVEL, MultiXscale, and DOME4.0, Lhumos (Learning HUb for MOdeling and Simulation) stands as a groundbreaking educational platform. It is specifically designed to support the upskilling of students, scientists, and industrial users in HPC applications within the material sciences domain.

Tailored for both early-career and advanced scientists, this e-learning platform consolidates a wealth of resources. It includes videos, lectures, codes, tutorials, seminars, and exercises covering diverse subjects such as electronic structure calculations, molecular dynamics, high-performance computing, and code optimization.

To introduce the Lhumos project and showcase its various sections and materials, an online presentation is scheduled for January 15 at 2 pm CET. The agenda for the event is as follows:

  • 2:00 pm CET: Welcoming by Sara Bonella, CECAM – MARVEL
  • 2:10 pm CET: Lhumos – A showcase of the platform by Roberto Bendinelli, MARVEL – CECAM – MaX
  • 2:30 pm CET: Question and Answer session

You can join the webinar online at https://epfl.zoom.us/j/65060242920?pwd=S3Raa0tqTWNoNDRpT2hJM3k0ZHhldz09.

Stay tuned for more upcoming events, workshops, and learning opportunities as Lhumos continues to bridge the gap between theory and application, academia, and industry.

EESSI support portal is now in place!

EESSI support portal is hosted in GitLab and provides support for:

  • Accessing and using the EESSI software stack
  • Software requests
  • EESSI test suite
  • Build-and-deploy bot
EESSI (European Environment for Scientific Software Installations)

For more information, please see https://www.eessi.io/docs/support

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