Two Post-Doctoral Research Assistantships Available
Division of Computing and Information Systems
University of Paisley

A research project which is to be funded by the Engineering and Physical Sciences 
Research Council (EPSRC), the Department of Trade and Industry (DTI), and industrial 
partners, to a total value of over �530K, will be conducted at the University of 
Paisley in Scotland for a period of three years. 
T
 he project aims to investigate the technologies required in software systems which 
will be able to provide effective detection and subsequent analysis of fraudulent 
activity within the general framework required of emerging fixed and mobile 
telecommunications applications such as electronic and mobile commerce.

Two postdoctoral positions are now available to investigate the application of machine 
learning and advanced data mining methods in the detection and analysis of anomalous 
and possibly fraudulent usage of fixed and mobile telecommunications applications such 
as electronic and mobile commerce. The project will involve the design and 
implementation of novel algorithms and systems to both discover and analyse emerging 
patterns of anomalous telecommunication system user activity.

Highly motivated candidates who have a publication record in, ideally, machine 
learning, data mining or artificial intelligence applications are encouraged to apply. 
Applicants should have, or shortly expect to obtain, a PhD in Computer Science.  
State-of-the-art computer hardware and software will be made available to the selected 
candidates, as will ample funding for travel to international conferences and 
meetings. 

Salaries will be on the R1A scale, starting at �20,066pa to �27,550pa.

The Applied Computational Intelligence Research Unit (ACIRU) is a young, ambitious and 
growing interdisciplinary research group within the University of Paisley. Within 
Scotland ACIRU have active and funded research collaborations with the University of 
Edinburgh, University of Stirling (http://www.cn.stir.ac.uk/incite/), the University 
of Glasgow and the University of Strathclyde and it forms part of a rich network of 
research establishments within which to work. 

For further information and informal enquiries please contact Mark Girolami 
([EMAIL PROTECTED], http://cis.paisley.ac.uk/giro-ci0) in the first 
instance. 

EPSRC & DTI Project
Data mining Tools for Fraud Detection in M-Commerce * DETECTOR
http://cis.paisley.ac.uk/giro-ci0/projects.html

Abstract: The effective detection and subsequent analysis of the types of fraudulent 
activity which occur within telecommunications systems is varied and changes with the 
emergence of new technologies and new forms of commercial activity (e&m-commerce). The 
dynamic nature of fraudulent activity as well as the dynamic and changing nature of 
normal usage of a service has rendered the detection of fraudulent intent from 
observed behavioural patterns a research problem of some considerable difficulty. It 
is proposed that a common theoretical probabilistic framework be employed in the 
development of dynamic behavioural models which combine a number of prototypical 
behavioural aspects to define a model of acceptable behaviour (e.g. usage of a mobile 
phone, web-browsing patterns) from which inferences of the probability of abnormal 
behaviour can be made. In addition to these inferential models a means of visualising 
the observed behaviour and the intentions behind it (based on call r!
ecords, web activity, or purchasing patterns) will significantly aid the pattern 
recognition abilities of human fraud analysts. Employing the common probabilistic 
modelling framework which defines the 'fraud detection' models visualisation tools 
will be developed to provide meaningful visual representations of dynamic activity 
which has been observed and visualisations of the evolution of the underlying states 
(or user intentions) generating the observed activity. The development of detection & 
analysis tools from the common theoretical framework will provide enhanced detection 
and analysis capability in the identification of fraud.

M.A.Girolami
School of Communication and Information Technologies 
University of Paisley 
High Street 
Paisley, PA1 2BE 
Scotland, UK 
  
Tel:  +44 - 141 - 848 3317  
Fax: +44 - 141 - 848 3542 
Email: [EMAIL PROTECTED] 






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