• University of Glasgow Featured PhD Programmes
  • Ross University School of Veterinary Medicine Featured PhD Programmes
  • University of Manchester Featured PhD Programmes
  • Coventry University Featured PhD Programmes
  • University of Birmingham Featured PhD Programmes
  • FindA University Ltd Featured PhD Programmes
  • Lancaster University Featured PhD Programmes
Ludwig-Maximilians-Universität Munich Featured PhD Programmes
Imperial College London Featured PhD Programmes
EPSRC Featured PhD Programmes
Coventry University Featured PhD Programmes
European Molecular Biology Laboratory (Heidelberg) Featured PhD Programmes

Big Data Analytics for Industrial Application

This project is no longer listed in the FindAPhD
database and may not be available.

Click here to search the FindAPhD database
for PhD studentship opportunities
  • Full or part time
    Dr Z Skaf
    Prof I jennions
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Qualification type: PhD
Location: Cranfield
Funding for: Self-funded Students
Duration of study: Full Time- three years fixed term
Start date: as soon as possible
Supervisors: Dr Zakwan Skaf and Prof Ian Jennions
Ref: CRAN1139


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.

Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2014 (REF) has recognised 81% of Cranfield’s research as world leading or internationally excellent in its quality. Every year Cranfield graduates the highest number of postgraduates in engineering and technology in the UK (Source: Higher Education Statistics Agency Ltd). Cranfield Manufacturing is one of eight major themes at Cranfield University. The manufacturing capability is world leading and combines a multi-disciplinary approach that integrates design, technology and management expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research.

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

How to apply:
Before completing the application documentation please contact Dr Zakwan Skaf [email protected] 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
E: [email protected]

Funding Notes

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


Cookie Policy    X