PhD Studentship: Big Data Analytics for Industrial Application

Cranfield University

Funding for: Self-funded Students

Duration of study: Full Time- three years fixed term

Start date: October 2016 (ideally, or as soon as possible)

Application deadline: Ongoing until a suitable candidate is identified

Interview date: To be confirmed

Supervisors: Dr Zakwan Skaf and Prof Ian Jennions

Project information

Big Data analytics has attracted intense interest from both academia and industry recently for its attempt to extract more useful information and knowledge from Big Data. Big Data analytics will help to develop more advance diagnosis and prognosis technologies, and, consequently, improve maintenance decision making. Currently, machine leaning exists as the most promising technologies of big data analytics in industrial problems.  

This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens, unknown correlation, and other useful information for diagnosis and prognosis solutions which leads to enhance reliability, maintainability and readiness of the selected system.

The student will have the opportunity to work with experts in the data analytics and condition monitoring field, as well as being part of our strong and dynamic research centre at Cranfield University.

About the host University/Centre

The Integrated Vehicle Health Management (IVHM) Centre is a major collaborative venture at Cranfield, started in 2008, with funding from the East of England Development Agency (EEDA); a consortium of core industrial partners, (Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD and Alstom); and from EPSRC. The investment, over the first 5 years of operation, was approaching £10M. We are now in our eighth year of operation and the Centre has grown into other sectors (rail, energy, health and agriculture), and is financially self-sustaining; many of the partners (and others) are funding Applied Research projects and there is a growing revenue from EPSRC, TSB and EU funded work

Entry requirements:

  • A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, and manufacturing) with a minimum 60% mark in the Project element or equivalent with a minimum 60% overall module average.
  • the potential to engage in innovative research and to complete the PhD within a three-year period of study.
  • a minimum of English language proficiency (IELTS overall minimum score of 6.5).

Also, the candidate is expected to:

  • Have excellent analytical, reporting and communication skills
  • Be self-motivated, independent and team player
  • Be genuine enthusiasm for the subject and technology
  • Have the willing to publish research findings in international journals 


This studentship is available to all UK/EU and International students.

How to apply:

Before completing the application documentation please contact Dr Zakwan Skaf for an initial informal discussion about this opportunity. Please include the keyword PhD Studentship-Self Funding in the subject field.

If you are eligible to apply for this research studentship, please complete the online application form

For further information contact us today:
T: 44 (0)1234 758008

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