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About

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This machine learning for materials training course is being run by the Physical Sciences Data Infrastructure (PSDI) initiative in collaboration with AIchemy, with support from STFC-SCD, PSDS, CCP5 and CCP9 as a follow up to the very popular 2023 Machine learning for Atomistic Modelling Autumn School. This training is targeted towards PhD students, in particular those in the Materials and Molecular Simulations field, who have experience of coding but are not highly experienced with machine learning. The aim of this training is to introduce attendees to the latest methods of machine learning for the atomistic simulation of materials.

This training will encompass a number of talks and practical sessions, focusing on the basics of machine learning, machine learning interatomic potentials and graph neural networks. There will also be the opportunity for attendees to present a poster on their work.

Learning outcomes

Awareness of the state-of-the-art methods for machine learning for atomistic and molecular simulations Hands on experience of using machine learning for atomistic and molecular simulations

Pre-requisites

Students attending this course must already have a foundational level of Python experience and hands on experience of using Python in their research. You will be expected to provide your own laptop for the training course, although software installation will not be required. A letter of support will be required from your supervisor alongside your application, this will be requested by email following your application. This letter of support is to show the backing of your supervisor to attend the training and must be completed for your application to be assessed.

NOTE Emails of initial acceptance for the school will go out 13th of January 2025. Please check your JUNK/SPAM folders. If you did not receive one you may be on the reserve list. Please confirm your place by xxx.

NOTE we are aware of various scam emails going around offering accommodation and various help. Please ignore them.

Timelines & Fees

The application deadline is 1st December 2024. Supervisors will be contacted for a letter of support following your application. All letters of support must be submitted by 6th December. You will be informed of the outcome of your application on 13th January 2025, you will have to accept your place within 1 week and payment is required by 16th February 2025.

Food and 4 nights accommodation (Travelodge Warrington) is included in the £350 fee paid for this event, travel to Daresbury (and public transport to /from the lab) is not included and will need to be covered by the attendee. If we are able to secure additional sponsorship for this event we will reduce the fee. Please note: places on this course are limited and in the event of oversubscription to the training course we will favour a diverse group of attendees.

Key dates

  • Registration opening: 1st of November 2024
  • Application deadline: 1st of December 2024
  • Acceptance decision: 13th of January 2025
  • Accept place: 20th of January 2025
  • Fee payments: 16th of February 2025

Organising Committee

  • Keith Butler, University College London
  • Reinhard Maurer, University of Warwick
  • Alex Ganose, Imperial College London
  • Ioan-Bogdan Magdău, Newcastle University
  • Chris Mellor, Imperial College London
  • Alin-Marin Elena, Scientific Computing Department STFC
  • Nicola Knight, University of Southampton

Sponsors

psdi Aichemy ccp5 cecam ccp9 cosec

Code of Conduct

We value the participation of everyone and want to ensure that everyone has an enjoyable and fulfilling experience, both professionally and personally. Accordingly, all participants of the CCP5 Summer School are expected to always show respect and courtesy to others. The Organising committee and its partners strive to maintain inclusivity in all of our activities. All participants (staff and students) are entitled to a harassment-free experience, regardless of gender identity and expression, sexual orientation, disability, physical appearance, body size, race, age, and/or religion. Harassment in any form is not acceptable for any of us.

We respectfully ask all attendees of the CAMML School to kindly conform to the following Code of Conduct:

  • Treat all individuals with courtesy and respect.
  • Be kind to others and do not insult or put down other members.
  • Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate.
  • Harassment includes, but is not limited to, offensive verbal comments related to gender, sexual orientation, disability, physical appearance, body size, race, religion, sexual images in public spaces, deliberate intimidation, stalking, following, harassing photography or recording, sustained disruption of discussions, and unwelcome sexual attention.
  • Participants asked to stop any harassing behaviour are expected to comply immediately.
  • Contribute to communications with a constructive, positive approach.
  • Be mindful of talking over others during presentations and discussion and be willing to hear out the ideas of others.
  • All communication should be appropriate for a professional audience, and be considerate of people from different cultural backgrounds. Sexual language and imagery are not appropriate at any time.
  • Challenge behaviour, action and words that do not support the promotion of equality and diversity.
  • Arrive at the events punctually where possible.
  • Show consideration for the welfare of your friends and peers and, if appropriate, provide advice on seeking help.
  • Seek help for yourself when you need it.

please report any issues to alin-marin.elena@stfc.ac.uk