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Sensing tribology within heavy machines

  • Full or part time
  • Application Deadline
    Friday, May 01, 2020
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Supervisor: Robert Wood
Co-supervisor Terry Harvey

Project description

This PhD is aligned with a major EPSRC funded research being conducted at the national centre for advanced tribology at Southampton (nCATS) in collaboration the machine learning and sensors research groups in ECS. The project will develop the next generation wear sensor for heavy machines in partnership with Shell, GE Aviation, Schaeffler and Senseye. Such sensors with embedded electronics that will allow far better spatial and temporal resolution of tribological contact decay (surface, subsurface and lubricant). Data outputs would be fed into machine learning algorithms for robust trend recognition and life prediction. The sensor would give more time to react and detect unusual and non-linear wear trends. Work at external companies is envisaged for testing the new sensors in their labs or in vehicles to show benefits of sensors to understanding distress of components/lubricant under test.

If you wish to discuss any details of the project informally, please contact Robert Wood, nCATS Research Group, Email: , Tel: +44 (0) 2380 594881.

Entry Requirements
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).

Closing date: applications should be received no later than 31 August 2020 for standard admissions, but later applications may be considered depending on the funds remaining in place.

Funding: full tuition plus, for UK students, an enhanced stipend of £15,009 tax-free per annum for up to 3.5 years.

How To Apply

Applications should be made online here selecting “PhD Engineering and Environment (Full time)” as the programme. Please enter Robert Wood under the proposed supervisor.

Applications should include:
Curriculum Vitae
Two reference letters
Degree Transcripts to date
Apply online:

For further information please contact:

How good is research at University of Southampton in General Engineering?

FTE Category A staff submitted: 192.23

Research output data provided by the Research Excellence Framework (REF)

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