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Automated Big data analysis


Project Description

This project will focus on the task of automating data analysis tasks, particularly for numerical data but the techniques developed could be applied to other domains such as textual data analysis. The data mining process currently requires human interaction and guidance throughout the process, and this project will look to exploit artificial intelligence techniques in order to allow the automation of the data analysis and feature extraction tasks.

The project will build on existing research work in this area, and the problem can be broken down into a number of distinct but important parts. The identification of important and irrelevant features in a dataset is an important task and one that cannot currently be undertaken in an automated manner. This task can be complicated when the features for a given class are different for different classes. The process developed needs to be able to take this into account and automatically identify the features for the given classes. In addition the process needs to be able to automatically classify the samples into the correct classes. This classification needs to be undertaken using artificial intelligence methods so that when classification is not successful, the decisions that the method has made can be investigated in order to change the input features in some way so that the next iteration will result in a different classification. The purpose therefore is to identify an iterative process that will learn which features are important in an automated manner.

The overall methodology developed will be tested against synthetic and also real world datasets.

Candidates should have (or expect to achieve) a UK honours degree at 2.1 or above (or equivalent) in Engineering, Physics or Computational Science.

It is essential that the successful applicant has a background in computer coding, algorithms and data analysis.

APPLICATION PROCEDURE:

• Apply for Degree of Doctor of Philosophy in Engineering
• State name of the lead supervisor as the Name of Proposed Supervisor
• State ‘Self-funded’ as Intended Source of Funding
• State the exact project title on the application form

When applying please ensure all required documents are attached:

• All degree certificates and transcripts (Undergraduate AND Postgraduate MSc-officially translated into English where necessary)
• Detailed CV

Informal inquiries can be made to Dr A Starkey () with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Postgraduate Research School ()

Funding Notes

This project is advertised in relation to the research areas of the discipline of Engineering. The successful applicant will be expected to provide the funding for Tuition fees, living expenses and maintenance. Details of the cost of study can be found by visiting View Website. THERE IS NO FUNDING ATTACHED TO THIS PROJECT.

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