Funded PhD Opportunity BTIIC-01: Autonomous abnormality detection for informed data-driven decision making

This opportunity is now closed.

This project is funded by: BT Ireland Innovation Centre (BTIIC) Invest NI

Subject: Computer Science and Informatics

Summary

BT Ireland Innovation Centre:

This studentship is one of twelve such PhD studentships, offered in collaboration with British Telecom and tenable in the School of Computing, Faculty of Computing, Engineering and the Built Environment at Ulster University based at the Jordanstown campus. The studentships relate to different research topics in future telecommunication networks and services with a particular emphasis on Intelligent Systems, Future Big Data Analytics, Internet of Things (IoT), Cyber Security, Fixed and Mobile Network Services. They are part of the recently funded BT Ireland Innovation Centre (BTIIC) which is a collaborative project between BT and Ulster University, with a large presence in BT Belfast. BTIIC is an ambitious research and engineering project, initially running for 5 years, and funded by Invest Northern Ireland. It comprises two Research Workstreams: (i) Intelligent Systems, and (ii) IoT – Trust, Security and Dependability. The research topics proposed for the 12 studentships are in these broad areas.

Project summary: Increasingly, ICT service providers such as BT are rich in data across their networks, services and customers. This includes network performance data, sensor data, customer Quality of Experience (QoE), service data, fault data etc. which is growing as the world of IoT, customised services, and social media grows. Value can only be extracted from this data through the application of analytics leading to a growing reliance on people skilled in data science which represents a serious bottleneck for businesses.

This PhD will focus on developing and extending previous work on autonomous abnormality detection for cloud applications, based on predictive modelling of KPIs for multi-layer architectures.  The approach will be extended to have a wider applicability to areas such as IoT, Home-hub, and customer behaviours. The use of techniques for multivariate time-series prediction and change point detection will also be explored.

Additional Application Information: On the application form applicants should select one main BTIIC project and a maximum of two further project titles in which they are interested. During the lifetime of the project there will be opportunities to work with BT Belfast Global Development Centre and there also may be openings to spend a period of time as part of a related Internship at BT Adastral Park Research Laboratories in Martlesham, Suffolk, UK (see (http://atadastral.co.uk/).  Arrangements for the internship / visits will be made by the supervisory team of the PhD project in conjunction with BT, subject to satisfactory student academic performance on the project.

Essential Criteria

  • Upper Second Class Honours (2:1) Degree from a UK institution (or overseas award deemed equivalent via UK NARIC)

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • First Class Honours (1st) Degree
  • Masters at 70%

Funding

This project is funded by: BT Ireland Innovation Centre (BTIIC) Invest NI

The scholarships will cover tuition fees and a maintenance award of not less than £14,777 per annum for three years (subject to satisfactory academic performance). Applications are invited from UK, European Union and overseas students.

Other information

The Doctoral College at Ulster University

Launch of the Doctoral College

Current PhD researchers and an alumnus shared their experiences, career development and the social impact of their work at the launch of the Doctoral College at Ulster University.

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Key Dates

Submission Deadline
Friday 17 August 2018
Interview Date
Late August 2018

Contact Supervisor

Professor Sally McClean

Other Supervisors

Apply online

Visit https://www.ulster.ac.uk/applyonline and quote reference number #242372 when applying for this PhD opportunity