[Job-offers-cs] Research Fellow in Mathematical Optimization for Machine Learning

Pekka Orponen pekka.orponen at aalto.fi
Sun Apr 30 17:22:35 EEST 2023


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Subject: 	[AALTO WARNING: POSSIBLE SPAM] [DMANET] Research Fellow in 
Mathematical Optimization for Machine Learning
Date: 	Mon, 24 Apr 2023 09:20:52 +0000
From: 	Alain Zemkoho via dmanet <dmanet at zpr.uni-koeln.de>
Reply-To: 	Alain Zemkoho <A.B.Zemkoho at soton.ac.uk>
To: 	dmanet at zpr.uni-koeln.de



Applications are invited for a Research Fellow in Mathematical 
Optimization for Machine Learning, to be based in the School of 
Mathematical Sciences at the University of Southampton. The post is a 
key part of a new research project funded by the Engineering and 
Physical Sciences Research Council (EPSRC).

Location: Highfield Campus
Salary: £34,314 to £37,386 Per annum
Full time for 1 year - extension possible if further funding is secured
Closing date: Saturday 20 May 2023
Interview date: To be confirmed
Reference: 2261823PJ

This project is part of an initiative between the University of 
Southampton and University College London, with IBM UK as industrial 
partner, to bring together bilevel optimization and machine learning 
experts to explore the most tractable ideas to build optimization theory 
and numerical schemes to address timely problems at the intersection of 
bilevel optimization and machine learning. The aim of this project, as 
the first step of this collaboration framework, is to review the 
literature to build a picture of the potential of bilevel optimization 
in machine learning. This work will therefore set the foundation of this 
initiative with the development of basic theoretical and numerical 
results for a better understanding of the structure of such problems.

For more details on the project and on how to apply, see here: 
https://jobs.soton.ac.uk/Vacancy.aspx?ref=2261823PJ>
Informal enquiries can be made at any time to Dr Alain Zemkoho 
(a.b.zemkoho at southampton.ac.uk) or Professor Massimiliano Pontil 
(m.pontil at cs.ucl.ac.uk).
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