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PhD Studentship: Re-imagining Engineering Design

Loughborough University - Mechanical, Electrical and Manufacturing Engineering

Qualification Type: PhD
Location: Loughborough
Funding for: UK Students, EU Students, International Students
Funding amount: The studentship is for 3 years and provides a tax-free stipend of £18,622 per annum for the duration of the studentship plus tuition fees.
Hours: Full Time
Placed On: 21st March 2024
Closes: 14th May 2024
Reference: FP-CTS-2024
 

Shape, topology and chemistry of materials and structures are the ingredients to achieve multifunctionality. Combining mechanical and thermal, or permeability and bio-instructive properties in the same high-performance product require novel design, manufacture, and validation techniques, both in silico and experimentally. Traditionally this process takes a lot of time, it is slow, and often the decision to progress from design concepts to prototype is taken without a complete set of information.

Wouldn’t it be great to have a “cyber engine” that could guide the design and manufacture stages, instead of having to rely on trial-and-error tests? Could Machine Learning-based tools help process parameter optimisation? This will lead to right-first time product realisation, with the corresponding efficiencies in capital investment, saving time and minimising waste and resources consumed.

This project is seeking candidates with a profound interest in the design, manufacture and validation of high performing lightweight, multifunctional products. We are looking for candidates who are interested both in the simulation aspects of the work as well as the experimental work. The candidate will be joining a multidisciplinary team in a lab where we design, make and test materials and structures.

This PhD will expose the successful candidate to a myriad of news techniques and much sought-after skills demanded by Industry, including the following:

Design of experiments, data harvesting/analysis and interpretation of results to derive insight.

Development of novel processing manufacturing techniques that allow the realisation of new design solutions

Modelling techniques at the macro scale, that can inform the direction of experimental activity (e.g. finite element simulations and numerical computations)

Physical, mechanical and materials characterisation techniques

Data-driven approaches to aid process parameter optimisation

Management (including self-management) techniques, scaffolded by the ‘Transition Zone’ ethos that supports Researchers’ professional development.

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