Research Assistant/Associate in Data Driven Quality Assurance in Additive Manufacturing

Campus: South Kensington, London

Do you want to be at the forefront of the next industrial revolution? We have an exciting opportunity for you to develop additive manufacturing (AM) technology for real-world engineering applications and push the frontiers of smart digital manufacturing and industry 4.0.

AM (3D printing) is not just for prototyping; it is revolutionising how real-world products are designed and made. AM enables better performing and more efficient designs with reduced manufacturing waste, lower cost, and shorter lead times. It is a key emerging technology enabling innovation in many sectors, from clean energy to healthcare, aerospace, and automotive. However, for sectors to benefit from all AM has to offer it is necessary to demonstrate that AM parts are of the highest quality.

We have UKRI and industrial funding to develop and validate methods to qualify metal AM parts for high-performance and safety-critical applications. The project uses high-speed camera-based systems to observe melt pool behaviour in a metal laser powder bed fusion machine and data driven methods to predict defect occurrence. The overall aim is to validate material quality on-the-fly and move towards a qualify-as-you-build paradigm where each printed part comes with a digital defect twin.

Duties and Responsibilities

You will be working within the Department of Mechanical Engineering to develop and validate tools to qualify additive manufacturing parts. This will require the use of laser powder bed fusion metal printing equipment, bespoke in-situ monitoring equipment and material/mechanical characterisation equipment. You will be processing large data sets to interpret trends, developing data driven methods to detect problems in the manufacturing process and critically evaluating those methods to insure they are robust enough for application “on the shop floor”.

Skills, knowledge and experience

• Ideally you will have, or be close to completing, a PhD in a relevant area, or have equivalent experience.
• Knowledge of Additive Manufacturing and/or Non-Destructive Evaluation (NDE) methods is highly desirable but not essential.
• Experience of image processing, statistical methods and/or machine learning methods is desirable.
• Practical experience with a range of techniques, including LPBF machinery, X-ray CT scanning, high-speed and infra-red cameras would be advantageous.
• You should be skilled with data analysis in Python, MATLAB or similar programming language.
• We are hiring a number of staff to cover these areas and you are not expected to be an expert in all areas. If you have experience in one or more of the above areas and a strong desire to learn you are encouraged to apply.

Key information:

This is a fixed term position for up to 24 months.

Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £36,694- £39,888 per annum.

Queries relating to the position should be directed to Dr Paul Hooper at paul.hooper@imperial.ac.uk.

To apply, please click “APPLY NOW” to go through to the online application form. Should you have any queries regarding the application process please contact ME-HR.Requests@imperial.ac.uk.

We are committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment for all. We therefore encourage candidates to apply irrespective of age, disability, marriage or civil partnership status, pregnancy or maternity, race, religion and belief, gender identity, sex, or sexual orientation. We are an Athena SWAN Silver Award winner, a Disability Confident Leader and a Stonewall Diversity Champion.

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