[Forum SIS] PhD opportunities, Oxford-Imperial StatML

[Stefano Favaro]

Ricevo e inoltro.

Cordial saluti,
Stefano Favaro


**** Inizio messaggio inoltrato ****

Da: Patrick Rebeschini <patrick.rebeschini a stats.ox.ac.uk>
Oggetto: PhD opportunities, Oxford-Imperial StatML 
Data: 5 novembre 2019 23:45:22 CET
A: "stefano.favaro a unito.it" <stefano.favaro a unito.it>

RE: PhD opportunities in Modern Statistics and Statistical Machine Learning at Imperial and Oxford. Deadline for first application round: November 15.

Are you interested in modern statistics and machine learning? Do you have a background in Maths, Statistics or related areas? If so then apply to the StatML CDT! 
StatML is a new Centre for Doctoral Training (CDT) based at Imperial College London and the University of Oxford. 
We offer a transformative style of doctoral training, leading towards a PhD / DPhil, which provides opportunities to: 
	• explore new research areas using modern statistical methods and machine learning;  
	• make real scientific, societal and industrial impacts with your research; 
	• experience and engage in peer to peer learning;  
	• be involved in cohort based training;  
	• work directly with leading industrial partners;  
	• receive exposure to cutting edge researchers in two world-leading universities. 
We will offer about 15 studentships for entry in October 2020. Each student will be funded with a grant for four years of study. Typically, the funding is available for Home/EU students – we expect to have two admissions rounds with submission deadlines of 15 November 2019 and 24 January 2020.  
There are very limited funding opportunities for overseas students (see the website for details). 
StatML is funded by EPSRC with support from industrial partners. 
Please visit the StatML website to find out more: https://statml.io/ <https://statml.io/>


Stefano Favaro
University of Torino and Collegio Carlo Alberto
http://sites.carloalberto.org/favaro/

-------------- parte successiva --------------
Un allegato HTML è stato rimosso...
URL: <http://www.stat.unipg.it/pipermail/sis/attachments/20191106/9a739d05/attachment.html>