Date: Thu, 19 Jun 1997 18:29:04 +0100
From: cs0jta@isis.sunderland.ac.uk (John Tait)
Message-Id: <199706191729.SAA00277@isis.sunderland.ac.uk>
To: ai+ai-predoc@cs.cmu.edu
Subject: Predoc: Ph.D. Studentship
Sender: ai@A.GP.CS.CMU.EDU


EPSRC CASE STUDENTSHIP,
UNIVERSITY OF SUNDERLAND, U.K. IN COLLABORATION WITH TGE LTD

An EPSRC CASE studentship is available to work in the areas of intelligent 
forecasting systems. The aim of the project is:
To research and develop intelligent forecasting techniques; particularly 
with reference to low volume sales products
To develop novel algorithms which will utilise expert system and Bayesian 
approaches to solve low volume forecasting problems
To experiment with these techniques within TGE's software product
To develop a new, more intelligent, version of  the software

The CASE student will undertake research work in the areas of intelligent 
forecasting, based on previous work undertaken at the University of 
Sunderland and elsewhere. The aim will be to develop a system which will use 
expert knowledge and beliefs as well as sales data to produce a more 
reliable forecast. This will involve extensive collaboration between the 
University and the company, TGE. The ultimate aim is to design and build new 
sophisticated self-learning and forecasting functionality into the system.

Candidates must have at least an upper second class honours degree in 
Computing and/or Mathematics or Statistics or equivalent. There are
restrictions on eligibility: in brief applicants need to be ordinarily
resident in the U.K., or be a refugee or have a similar connection
with the U.K.

Applications in the form of a CV before 30 June 1997, with two referees to:

Professor Peter Smith
School of Computing and Information Systems
University of Sunderland
St Peters Campus
St Peters Way
Sunderland SR6 0DD
U.K.

Tel +44 191 515 2773
Fax +44 191 515 2781
email peter.smith@sunderland.ac.uk


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