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ALLSTAT  August 2012

ALLSTAT August 2012

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Subject:

UCL Statistics - Fully Funded PhD Studentships (Methodology)

From:

Prof PJ Wolfe <[log in to unmask]>

Reply-To:

Prof PJ Wolfe <[log in to unmask]>

Date:

Sat, 25 Aug 2012 11:12:22 +0100

Content-Type:

text/plain

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text/plain (33 lines)

UCL invites expressions of interest in fully funded PhDs in Statistics, working with Professor PJ Wolfe and starting from 1st October 2012.  

Topics will be broadly focused on methodological aspects of statistical network analysis, some of which will be in concert with industrial partners, an example of which is described below.

Please send CVs (including a list of 3 academic references) to [log in to unmask]; prospective students whose applications will be taken forward will receive a follow-up email with further instructions.

* * *

Some PhDs may involve working with a world leading company which has purchasing data from over 350 million people in 28 countries. They process and analyse over a billion rows of data each week and have customer data spanning 5 years.  

The vast amount of loyalty card transaction data and market research attitudinal data allows a great depth of understanding in terms of what customers are doing and what they are thinking.

A typical supermarket sells 50,000 items across 100 categories.  When deciding on which  product to buy factors such as: price, quality, brand, recommendation, offers etc. all play their part in the decision-making process for a customer.  By understanding the complex interaction of these factors, customers can be treated as individuals, and their shopping experience improved and made more relevant to them.

This is a fantastic chance to explore the cutting edge of extracting real-world insight into customer behaviour from the increasingly massive and complex data available.

We are happy to consider UK/EU candidates from any relevant scientific discipline.  However, the successful candidate should possess:

* Strong academic background (based on educational qualifications)

* Strong quantitative skills including data manipulation strong research skills (especially in large scale quantitative studies)

* Strong communication skills – ability to explain complex techniques to people who are not technical

* Creative problem solver 

* Passionate about Customer Behaviour Analytics and retail

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