4 March – 7 March 2024
The SENSE CDT is running a training course for ‘Machine Learning and AI’ from 4 – 7 March 2024, in person, at the University of Leeds. We are delighted to be able to offer places for up to 10 UK based PhD students to attend.
Successful applicants will join the NERC SENSE CDT PhD students on the training, providing an excellent opportunity for PhD students across the UK to network. The SENSE CDT is on satellite data in environmental science, from which most of the examples will be taken.
The teaching week is a mixture of theory followed by practical exercises, keynote speakers, and transferable skills development.
|Mon||Machine Learning AI techniques practical: classification of images, textural description||AI techniques practical: contd Keynote: New directions of AI, Prof David Hogg|
|Tues||Agent-based models Introduction to Urban Analytics Urban systems machine learning practical 1/2||Urban systems machine learning practical 2/2 “Dos and Don’ts of presenting”, Prof Jurgen Neuberg|
|Wed||The role of ATI and overview of LIDA Unsupervised classification of clouds lecture & practical||Unsupervised classification of clouds summary Keynote: Using science to influence policy, Dr Cat Scott|
|Thurs||Scientific Machine Learning Using machine learning in EO Alan Turing Institute lecture|
The course is free to successful applicants and overnight accommodation will be provided, Monday – Wednesday. However, attendees will need to book their own travel and cover their travel and subsistence costs whilst on the course.
Tea, coffee and refreshments will be provided during morning and afternoon breaks.
Students will be required to bring their own laptops. Information will be given prior to the training on any software downloads required.
The training will take place, at the University of Leeds, National Centre for Atmospheric Science, Fairbairn House, 71-75 Clarendon Rd, Woodhouse, Leeds LS2 9PH.
Attendees are expected to attend all sessions.
Applicants must be:
- in the first or second year of their PhD studies
- studying in an associated field, with a strong mathematical and computing background
- able to demonstrate that the training is relevant to their PhD research and is unavailable at their home institution.
How to apply
Applicants need to complete the following form https://forms.gle/vDbmE6gEzyZswPjn6
The deadline for applications is 1 January 2024 (23:59)
Successful applicants will be informed shortly afterwards.
For informal enquiries please contact firstname.lastname@example.org