Research Associate in Graph-Based Machine Learning

University College London - UCL Computer Science

In the 2014 Research Excellence Framework (REF) evaluation UCL was ranked in first place for Computer Science, out of 89 Universities assessed, and considerably ahead of other Institutions. 61% of its research work is rated as world-leading (the highest possible category) and 96% of its research work is rated as internationally excellent.

The Research Associate will be responsible for carrying out research in graph-based machine learning. The Research Associate will be working in collaboration with Mark Herbster and Peter Bentley.

This post is available until 31 March 2019 in the first instance.

The successful candidate will have a PhD in Mathematics, Computer Science or Physics, with ideally an emphasis on Machine Learning. Experience in proving performance guarantees in both the online and batch settings as well as programming experience in Neo4j and Java is valuable. They will also have knowledge of research techniques and methodologies. Candidates should be committed to high quality research and ideally have experience of working in a research environment.

UCL vacancy reference: 1690777

Applicants should apply online. To access further details about the position and how to apply please click on the ‘Apply’ button below.

If you have any queries regarding the vacancy or the application process, please contact Mark Herbster, ( m.herbster@cs.ucl.ac.uk ).

Closing Date: 14 December, 2017. Latest time for the submission of applications: 23:59.

Interview Date: 19 December 2017

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