09 MAR 2021
From 15 – 19 February 2021, over 80 participants attended the online LENS Machine Learning School. The school, which was targeted towards neutron and muon facilities staff, offered a gateway for beginner and intermediate coders to get into machine learning, providing an overview of modern and traditional machine learning techniques alongside neutron or muon based applications.
The Machine Learning School, organised collaboratively by the LENS initiative, was run by lecturers from facilities across Europe, including ISIS, PSI, ESS, ILL, and MLZ, with additional support from the STFC’s SciML group and the Jülich Supercomputing Centre.
The hands-on lectures covered a range of topics, from the very basics of how a neural network operates, to training a neural network to play Mrs Pac-Man (with a fair dose of more traditional methods inbetween!).
Resources from the School, including recordings of most of the lectures, are available online for all to access. Anyone with an interest in machine learning is encouraged to explore the lecture material and join the Slack channel for the LENS Machine Learning School for hints, tips and discussion on the projects going on across the European neutron and muon sources.
Jos Cooper, ISIS, email@example.com
- The ESFRI Roadmap for Research Infrastructures in Europe has influenced European and national strategies, policies and funding since the first edition was launched in 2006. The latest roadmap, published on 7 December 2021, recognises the important role of the LENS Initiative in bringing together European analytical facilities to "identify synergies and opportunities for closer collaboration" and "improve the cooperation of various communities and enhance user facilities".
- The first call for applicants for the GNeuS fellowship programme is open from 1 November 2021 until 15 January 2022.
- In the context of the 26th UN Climate Change Conference (COP26), LENS has compiled a variety of resources demonstrating how neutron scattering methods are being applied in energy, materials, and environment research, to help reduce our impact on the global climate.