Dear Colleagues,

We are pleased to announce the ‘Machine Learning for Atomistic Modelling Autumn School’; this machine learning for materials training course is being run by the Physical Sciences Data Infrastructure (PSDI) initiative in collaboration with PSDS, AI4SD, STFC-SCD and CCP5. This training is targeted towards PhD students, particularly 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 applied to atomistic simulation of materials and provide hands on experience of using machine learning for atomic and molecular simulations. There will also be the opportunity for attendees to present a poster on their work.

https://www.psdi.ac.uk/event/machine-learning-autumn-school-2023/

Date of Event: 18th 12:00 – 20th September 14:00

Location: Daresbury Laboratory, in person event

Fee: £100 (covers 2 nights accommodation and catering)

Pre-requisites: Students will be expected to bring their own laptop, to have a decent level of coding experience (see event page) and provide a letter of support from their supervisor

Applications are now open for this training course. The application deadline is 30th June 2023 (including letter of support). You will be informed of the outcome of your application on 14th July, and payment is required by 18th August.

You can find all the information on our event page: https://www.psdi.ac.uk/event/machine-learning-autumn-school-2023/

Please pass this message along to any people who may be interested in attending. Please note: places on this course are limited and in the event of oversubscription for the training course we will favour a diverse group of attendees.

Regards,
Organising committee