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Big Data Analytics and Data Stream Mining

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  • Full or part time
    Dr Stahl
    Dr DiFatta
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

The technological advances in data acquisition hardware and data storage have led to a growth in the size of datasets used by science and industry, this known as the Big Data phenomenon. However, the sheer size of data and the speed at which data is generated is challenging our analysis methods in computational as well as in qualitative terms of the analysis results. We are supervising PhD candidates that will work to advance data mining algorithms for Big Data processing. The PhD candidate is expected to address some of the following issues: development of parallel data mining algorithms and techniques, development of data analytics algorithms that process data in real time, formation of sentiment analysis techniques on unstructured data, and the advancement of data mining techniques for smart mobile devices.

Duration: 36 months

Funding Notes

We welcome applications from self-funded students worldwide for this project.

Eligibility

Applicants should have completed a degree in Computer Science or a strongly related discipline. Strong computing and mathematical skills are preferable. Experience in any field related to the project, such as data mining, machine learning and parallel and distributed computing, are desirable.

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