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AIM/MCRN Summer School: Week 6

August 2, 2020

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AIM/MCRN Summer School: Week 5

July 26, 2020

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Professor Christopher K.R.T. Jones — Recipient of the 2020 MPE Prize


Professor Chris Jones is the Bill Guthridge Distinguished Professor in Mathematics at the University of North Carolina at Chapel Hill and Director of the Mathematics and Climate Research Network (MCRN). The 2020 MPE Prize recognizes Professor Jones for his many significant contributions to climate science and the mathematics of planet Earth.

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Workshops

Machine Learning for Environmental Sciences 2019

General

Organized by British Antarctica Survey

https://www.eventbrite.co.uk/e/workshop-machine-learning-for-environmental-sciences-tickets-60865256621

06/17/2019 - 06/18/2019

British Antarctica Survey, Cambridge, UK

The British Antarctic Survey and the University of Cambridge are hosting a 2 day (lunch-to-lunch) workshop on Machine Learning for Environmental Sciences, to be held at the British Antarctic Survey on Monday 17th to Tuesday 18th June.

This conference follows on from the 2017 conference on “Environmental Science in the Big Data Era” hosted by BAS and the University of Cambridge and aims to bring together Machine Learning and Environmental researchers, with a view to establish new collaborations and strengthen existing networks. In particular we encourage Early Career Researchers to attend and offer a limited number of reduced price tickets for ECR’s (researchers within 10 years of their most recent degree).

The workshop will feature a keynote talk from Claire Monteleoni (University of Colorado), as well as presentations on both recent achievements and proven concepts in the area, and more preliminary work and results.

The workshop will be followed by a ‘Hands-on Data Challenge’ session on the afternoon of Tuesday 18th following lunch, featuring practical examples of Machine Learning applied to Environmental Data Sets. The session is open to everyone and aimed at all levels of expertise. Please provide your own laptop, and we will provide access to suitable datasets and ensure expert support is available.

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