Two Post-Doctoral Research Assistantships Available

[Mark Girolami]

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. The 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 (mark.girolami at paisley.ac.uk,
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 records, 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: mark.girolami at paisley.ac.uk 






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