PhD Studentship: Electromagnetic Sensing for Intelligent Manufacturing and Advanced Materials

Project description

Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to extract far more information from EM measurements than ever before, creating new opportunities for fast, reliable, and quantitative non-destructive evaluation (NDE).

This PhD is focused on developing practical EM sensing solutions for real and future industrial challenges. You will design and test sensing systems that can inspect materials and components during and after manufacture. Key application areas include automated carbon fibre composite production—where rapid quality assurance is essential for aerospace structures—and metal components produced by additive manufacturing, where complex internal geometries and process-induced defects demand new inspection approaches.

The project combines modelling, sensor fabrication, experiment, and data analysis. You will work with a team of experts to develop predictive simulation tools, and create advanced data-processing methods that translate EM signals into clear, actionable information about material properties and defects. The emphasis is on solutions that can operate in realistic industrial environments, supporting automation and digital quality control.

You will join Dr Hughes’s EM Sensing group within Bristol’s Ultrasonics and Non-Destructive Testing Laboratory, with access to facilities including the National Composites Centre and the Isambard AI supercomputing platform. The PhD is a part of a UK-wide collaboration across five leading universities and more than 25 industrial partners, providing strong pull and support for real-world applications and opportunities to work closely with industry.

By the end of the project, you will have developed expertise in sensor design, experimental testing, modelling, machine learning, and industrial collaboration, positioning you to contribute directly to next-generation inspection technologies for aerospace, energy, advanced manufacturing, and healthcare.

Entry requirements:

Applicants must hold/achieve a minimum of a merit at master’s degree level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first-class undergraduate degree. Please note, acceptance will also depend on evidence of readiness to pursue a research degree.

Applicants with a Physics, Maths or Electrical Engineering background are encouraged to apply. An ideal candidate should also have a creative problem-solving mind-set and work well with others.

If English is not your first language, you need to meet this profile level:

Profile E

Further information about English language requirements and profile levels.

Applicants must hold/achieve a minimum of a merit at master’s degree level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first-class undergraduate degree.

Applicants with a Physics, Maths or Electrical Engineering background are encouraged to apply.

An ideal candidate should also have a creative problem-solving mind-set and work well with others.

If English is not your first language, you need to meet this profile level:

Profile E

Further information about English language requirements and profile levels.

Prior to submitting an online application, you will need to contact the project supervisor to discuss.

Online applications are made at http://www.bris.ac.uk/pg-howtoapply.

Please select Future Innovations in Non-Destructive Evaluation on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form.

For questions about the research topic, please contact Robert Hughes (Robert.hughes@bristol.ac.uk).

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