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Research Assistant in Structural and Algorithmic Graph Theory

Are you an early career researcher looking for your next challenge? Do you have a background in graph theory? Do you want to further your career in one of the UK’s leading research intensive universities?

This is an opportunity for a motivated researcher to work on the EPSRC grant EP/N019660/1 "Structure of Hereditary Graph Classes and Its Algorithmic Consequences". You will join the thriving Algorithms and Complexity Research Group at the School of Computing, University of Leeds, UK.

This project will focus on developing techniques for structural and algorithmic study of hereditary graph classes, with the aim of gaining insight into the boundaries of what is computationally feasible.         

You will have an undergraduate or masters degree in Computer Science or a closely allied discipline, or equivalent research experience. You will also have research experience including, but not limited to, structural graph theory, combinatorial optimization and graph algorithms.

To explore the post further or for any queries you may have, please contact: 

Prof. Kristina Vuškovic, Leader of Algorithms and Complexity Research Theme 

Tel: +44 (0)113 343 5443 or email: 

Further information

The Schools in the Faculty of Engineering & Physical Sciences are proud to have been awarded the Athena SWAN Bronze or Silver Award from the Equality Challenge Unit, the national body that promotes equality in the higher education sector. Our equality and inclusion webpage provides more information.

Location:  Leeds - Main Campus
Faculty/Service:  Faculty of Engineering & Physical Sciences
School/Institute:  School of Computing
Category:  Research
Grade:  Grade 6
Salary:  £27,511 to £32,817 p.a.
Post Type:  Full Time
Contract Type:  Fixed Term (Until 28 February 2021 (grant funding))
Release Date:  Wednesday 20 May 2020
Closing Date:  Tuesday 26 May 2020
Reference:  EPSCP1016
Downloads:  Candidate Brief  
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Athena Swan Bronze Award
Equality and Inclusion - Everyone Included, Everyone Involved
HR Excellence in Research