PhD Studentship Novel Optimisation Algorithms for Engineering Design (Rolls-Royce plc)

Ref: AACE-CED-105

Research group: Computational Engineering & Design, Faculty of Engineering and the Environment

Deadline: Applications will be accepted at any time until the position is filled.

A PhD studentship is now available to develop novel design optimisation algorithms within the Rolls-Royce University Technology Centre (UTC) for Computational Engineering at the University of Southampton.

Design optimisation techniques are employed throughout a wide range of engineering disciplines and aim to improve the performance of a component, or a system, in an automated manner. Previously the UTC has been actively involved in the development of cutting edge optimisation software and techniques for Rolls-Royce which have been used to improve the design of engine casings and combustors as well as compressor and turbine blades. To date, however, these efforts have focused mainly on the optimisation of either a single component or sub-system and not the engine as a whole. Naturally the optimisation of a complete system, be it a gas turbine, or indeed any other engineering system, will result in an optimisation problem with a large number of design variables of various types, requiring sophisticated computer based analysis such as FEA and CFD.

The successful candidate will therefore be expected to carry out fundamental research in the field of design optimisation and develop novel processes to help solve large scale optimisation problems employing FEA and CFD codes. The candidate will then apply the developed processes to real world engineering design problems in association with Rolls-Royce Plc.

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Students interested in this project should have a good first degree in a relevant field, should be highly motivated and have an aptitude for both programming and numerical work.

The studentship is funded by Rolls-Royce and is open to overseas applicants.

If you wish to discuss any details of the project informally, please contact Dr. David Toal, Computational Engineering & Design research group, Email: , Tel: +44 (0) 2380 59 7662.

To apply, please use the following website:

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