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Machine Learning and AI Workshop 15-16 January 2020

Cristobel Soares-Smith

Wednesday, 15 January 2020 at 10:00 - Thursday, 16 January 2020 at 16:00 (GMT)

Machine Learning and AI Workshop 15-16 January 2020

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Event Details

Machine Learning and AI Workshop 15-16 January 2020

 

Who: PhD students and postdoctoral researchers interested in modern data science and AI and how this is applied to physics and astronomy.

 

What: A 2-day workshop that consists of presentations and tutorials to ensure delegates get the chance to learn about modern methods and have the opportunity to get some hands on experience.

 

When: 15-16 January 2020

 

Where: Queen Mary University of London, Mile End Road, London

 

Numbers: Circa 30-40 delegates

 

This machine learning and AI workshop provides an overview of the use of modern data science and AI methods in the context of physics and related problems. It comprises lectures, practical tutorials and discussion sessions to allow participants to explore methods and help develop an understanding of what tools and methods work well under different circumstances.

 

The workshop will be beneficial to researchers working on data-rich theoretical and experimental projects, not just in astronomy and particle physics but also more general topics reflecting the pervasive nature of data science in society today. This will better equip graduates for their life after their PhD, in both academia and industry.

 

Requirements: A laptop computer is essential to follow the tutorial parts of this workshop.

 

This event is free (SEPnet pays for your accommodation and course fees) for SEPnet postgraduate researchers and travel expenses incurred can be claimed from your Physics Department.

 

Registration deadline: 11 December 2019

Do you have questions about Machine Learning and AI Workshop 15-16 January 2020? Contact Cristobel Soares-Smith

When & Where


Queen Mary University of London
Mile End Road
Bethnal Green
E1 4NS London
United Kingdom

Wednesday, 15 January 2020 at 10:00 - Thursday, 16 January 2020 at 16:00 (GMT)


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