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Digital Twin with application to smart manufacturing using electromagnetic pulse technology (EMPT)

   Brunel Centre for Advanced Solidification Technology (BCAST)

   Sunday, July 31, 2022  Funded PhD Project (UK Students Only)

About the Project

Applications are invited for a funded PhD studentship supported by the Institute of Digital Futures for the project titled: “ Digital Twin with application to smart manufacturing using electromagnetic pulse technology (EMPT)”starting 1st October 2022. Successful applicants will receive an annual stipend (bursary) of £18,062 plus payment of their full-time home tuition fees for a period of 36 months (3 years). Applicants must be eligible for home tuition fees either through nationality, residency (living in the UK for at least three years and not wholly for educational purposes) or other connection to the UK.

The successful applicants will join the internationally recognised researchers in the Department of Computer Science and Brunel Centre for Advanced Solidification Technology (BCAST).

 This multidisciplinary doctoral programme will be housed jointly by the department of Computer Science and Brunel Centre for Advanced Solidification Technology (BCAST), and will be co-supervised by Professor H. Assadi, Dr M. Zhou, and Dr D. Suleimenova in College of Engineering, Design and Physical Sciences.

 The successful candidate will join an interdisciplinary doctoral programme in Materials Engineering and Computer Science at Brunel University London. This exciting research project focuses on developing a digital twin of an advanced manufacturing technology (EMPT) which is currently being used for high-speed forming and joining of metals. The aim is to couple machine learning techniques to multiphysics-based models of EMPT to monitor, control, and optimise the manufacturing process. The research will include (1) multiphysics numerical simulation of EMPT to generate an information database for machine learning, (2) establish surrogate models that streamline the digital-twin environment, and (3) application of machine learning to analyse experimental and numerical data for EMPT optimisation. The student will have unique opportunities to receive specialised training to support their research, gain industrial experience through collaboration with manufacturing companies, become an expert in the field of physics-informed machine learning, and develop hands-on experience in electromagnetic pulse technology at the UK’s leading specialist centre in EMPT. This project parallels research activities in digital manufacturing in BCAST, department of Computer Science and the Institute of Digital Futures at Brunel. The successful candidate will be embedded in a vibrant research group dedicated to digital and intelligent manufacturing, including leading experts in digital manufacturing, machine learning and process modelling.

Applicants will be required to demonstrate their ability to:

·        A sound scientific/engineering background and understanding

·        Interest in electromagnetic pulse technology

·        Ability to learn independently and self-motivation

Please contact Professor Hamid Assadi at and Professor Abdul Sadka at   for an informal discussion about the studentships. 



Applicants will have or be expected to receive a first or upper-second class honours degree in an Engineering, Computer Science, Design, Mathematics, Physics, or a similar discipline. A Postgraduate Master’s degree is not required but may be an advantage.  

Desirable experience:

·        Experience in materials process modelling.

·        Experience with finite element modelling software.

·        Experience with machine learning software tools and programming languages.

would be advantageous. In addition, the applicant should be highly motivated, able to work in a team, collaborate with others and have good communication skills.

How to Apply

Please submit your application documents (see list below) in one PDF file by 31 July 2022

 to   Interviews will take place in August 2022.

·        Your up-to-date CV;

·        Your personal statement (300 to 500 words) summarising your background, skills and experience;

·        Your Undergraduate/Postgraduate Master’s degree certificate(s) and transcript(s);

·        Evidence of your English language skills to IELTS 6.5 (or equivalent, 6.0 in all sections), if appropriate;

·        Contact details for TWO referees, one of whom can be an academic member of staff in the College.

Remember to state the title of the project at the top of your personal statement. 

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