A PhD Position in Image Processing for Mechanical Component Degradation Analysis is available within the School of Applied Sciences, Cranfield University, UK. The PhD studentship is supported by EPSRC and Rolls-Royce, a fellowship up to £17,000 p.a. for 3 years plus UK/EU fees.
Description of the PhD Position
Cranfield University is seeking a highly motivated graduate to undertake this exciting research project. The PhD researcher will develop image processing and data fusion techniques to identify degradation in mechanical components (e.g. aero engine components) and visualize compounded degradation for ‘as maintained’ perspective. It is expected that the researchers will perform image processing of thermal and X-Ray images. The research will develop an experimental facility to characterise the type and extent of degradation during service.
Doctoral Training Centres
This higher research degree is associated with one of our Doctoral Training Centre, which is funded in part by the Research Councils and industry. A generic core skills training programme is provided for all research students. This is structured as a series of half day or full day events and acts as a social and networking forum to foster and develop Cranfield’s research student community.
Entry Requirements
Applicants should be classified as UK Home student and have a First or Second Class UK honours degree (or equivalent) in a relevant discipline such mechanical/aerospace/manufacturing/electronics/computer science and engineering. Knowledge or experience and an MSc in a relevant subject are highly desirable. Experience in image processing and software programme development will be preferable.
Application Procedure
For application procedure and other details please visit the Cranfield University webpage.
For further information contact:
School of Applied Sciences
T: +44 (0)1234 754086
E: appliedsciences@cranfield.ac.uk
Note, application deadline to the PhD Position in Image Processing for Mechanical Component Degradation Analysis, UK is 30 October, 2011.
Please mention scholarships4phd.blogspot.com on your application while applying for this scholarship.
© 2011 Research Grants.
Related Posts
Description of the PhD Position
Cranfield University is seeking a highly motivated graduate to undertake this exciting research project. The PhD researcher will develop image processing and data fusion techniques to identify degradation in mechanical components (e.g. aero engine components) and visualize compounded degradation for ‘as maintained’ perspective. It is expected that the researchers will perform image processing of thermal and X-Ray images. The research will develop an experimental facility to characterise the type and extent of degradation during service.
Doctoral Training Centres
This higher research degree is associated with one of our Doctoral Training Centre, which is funded in part by the Research Councils and industry. A generic core skills training programme is provided for all research students. This is structured as a series of half day or full day events and acts as a social and networking forum to foster and develop Cranfield’s research student community.
Entry Requirements
Applicants should be classified as UK Home student and have a First or Second Class UK honours degree (or equivalent) in a relevant discipline such mechanical/aerospace/manufacturing/electronics/computer science and engineering. Knowledge or experience and an MSc in a relevant subject are highly desirable. Experience in image processing and software programme development will be preferable.
Application Procedure
For application procedure and other details please visit the Cranfield University webpage.
For further information contact:
School of Applied Sciences
T: +44 (0)1234 754086
E: appliedsciences@cranfield.ac.uk
Note, application deadline to the PhD Position in Image Processing for Mechanical Component Degradation Analysis, UK is 30 October, 2011.
Please mention scholarships4phd.blogspot.com on your application while applying for this scholarship.
© 2011 Research Grants.
Related Posts
