Queen's University Belfast - School of Electronics, Electrical Engineering and Computer Science
|Salary:||£26,829 to £32,004 per annum|
|Contract Type:||Contract / Temporary|
|Placed on:||18th October 2016|
|Closes:||11th November 2016|
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This post is available until 31 December 2018 to work on a large R&D project with AllState NI on novel graph mining techniques for insurance fraud detection. The post holder is expected to lead, plan and deliver research activities focused on developing an integrated anomaly detection system to identify fraudulent insurance claims and point-of-sale frauds from multiple, heterogeneous data sources.
The role addresses key challenges presented by real-time fraud detection and prevention in large-scale heterogeneous claims systems, including data mining and analytics, and anomaly detection. More specifically, the research topics are on graph-based community detection and graph-based algorithms for discovering patterns and anomalies.
The successful candidate will be appointed to work on the topics listed above, but will also work together with the current Research Fellow on this project, as well as working with data scientists from Allstate to experimentally evaluate the proposed algorithms and other theoretical concepts and integrate functional components into Allstate’s testing environments as required.
Anticipated interview date: Tuesday 29 November 2016
Research Assistant: £26,829 per annum
Research Fellow: £32,004 per annum
Apply online at www.qub.ac.uk/jobs. For further information or assistance contact the Personnel Department, Queen’s University Belfast, BT7 1NN. Telephone (028) 9097 3044 or email on email@example.com.
The University is committed to equality of opportunity and to selection on merit. It therefore welcomes applications from all sections of society and particularly welcomes applications from people with a disability.
Fixed term contract posts are available for the stated period in the first instance but in particular circumstances may be renewed or made permanent subject to availability of funding.
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