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PhD Studentship (3 years) - Mining and Modernising Legacy Data Integration Pipelines

Aston University - College of Engineering and Physical Sciences

Qualification Type: PhD
Location: Birmingham
Funding for: UK Students
Funding amount: This studentship includes a fee bursary to cover the Home fees rate, plus a maintenance allowance of at least £15,609 in 2021/22 (subject to eligibility).
Hours: Full Time
Placed On: 20th September 2021
Closes: 1st February 2022
Reference: R210376

Closing Date: 1st February 2022 (or until the position is filled)

Supervisor: Dr Antonio Garcia-Dominguez, Dr Felipe Campelo

Project Reference: EPS_ Garcia-Dominguez_Beazley

Applications are invited for a three year Postgraduate studentship, supported by the College of Engineering and Physical Sciences, to be undertaken within the SEA Research Group at Aston University.  The successful applicant will join an established experimental group working on model-driven software engineering and self-adaptive computing. The studentship is offered in collaboration with the Beazley Group, a leading specialist insurer with decades of experience in providing clients with the highest standards of underwriting and claims service worldwide.

The position is available to start in either January or April 2022, subject to negotiation.

Financial Support

This studentship includes a fee bursary to cover the Home fees rate, plus a maintenance allowance of at least £15,609 in 2021/22 (subject to eligibility). This studentship is only available to Home students.

Background to the Project

The financial and insurance industries rely on the ability to integrate data from a large

variety of heterogeneous sources, building profiles about entities or feeding advanced

risk models, among other tasks. The volumes of data to be integrated are becoming

increasingly large, to the point where traditional overnight batch processing cannot

provide results quickly enough to allow for timely and informed decisions, and a stream-

oriented approach that reacts to incoming data in an incremental way is needed.

This thesis will study approaches to tackle the above challenges of integrating large

amounts of data from an increasingly diverse number of sources, by using stream-

oriented processing and AI-based approaches. The envisioned approach would start by

mining knowledge models from the existing legacy data integration pipelines, and using those knowledge models to derive a stream-oriented version of the process.

Person Specification

The successful applicant should have been awarded, or expect to achieve, a Masters degree in a relevant subject with a 60% or higher weighted average, and/or a First or Upper Second Class Honours degree (or an equivalent qualification from an overseas institution) in a relevant subject.  Preferred skill requirements include knowledge/experience of data mining, data integration, business intelligence, machine learning, stream processing, and/or model-driven software development.

We would particularly like to encourage applications from women seeking to progress their academic careers. Aston University is committed to the principles of the Athena SWAN Charter, recognised recently by a prestigious Silver Award to EPS, and we pride ourselves on our vibrant, friendly and supportive working environment and family atmosphere. 

Contact information

For formal enquiries about this project contact Dr Antonio Garcia-Dominguez by email at

Submitting an application

Details of how to submit your application, and the necessary supporting documents can be found here

*Applications must also be accompanied by a research proposal giving an overview of the main themes of the research as detailed in the Background to the Project section above.  This should demonstrate your understanding of the research area and how your knowledge and experience will benefit the project.

Please include the supervisor name, project title, and project reference in your Personal Statement.

If you require further information about the application process please contact the Postgraduate Admissions team at

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