PhD Studentship – Electromagnetic Sensing Manufacturing and Advanced Materials

PhD Studentship – Electromagnetic Sensing for Intelligent Manufacturing and Advanced Materials University of Bristol Bristol, England, United Kingdom General Description

The University of Bristol invites applications for a fully funded PhD studentship focused on advancing electromagnetic (EM) sensing technologies tailored for intelligent manufacturing systems and the development and characterisation of advanced materials. This research project is designed to address industrially relevant challenges by creating practical EM sensing solutions that can be deployed within modern manufacturing environments to improve in‑process monitoring, quality assurance and material performance understanding.

The successful candidate will undertake original research that combines experimental design, modelling and validation of EM sensing methods within a multidisciplinary engineering context. This opportunity situates the student within an internationally recognised research community, offering access to world‑class facilities and collaborations across academia and industry.

Applicants should hold, or expect to achieve, an upper second‑class honours degree (2:1) or equivalent in an appropriate discipline such as physics, electrical/electronic engineering, materials science, mechanical engineering or a closely related field. Demonstrated academic excellence and a strong interest in research are essential. International candidates are eligible to apply; funding terms may vary depending on residency status and programme regulations.

Specific doctoral programme admission requirements at the University of Bristol also apply.

Ideal candidates will possess a strong background in areas relevant to electromagnetic phenomena, sensor design, materials characterisation and/or intelligent manufacturing. Proficiency in analytical thinking, problem‑solving, and experimental and/or computational research methods is expected. Experience with electromagnetic simulation tools, programming (e.g. MATLAB, Python), laboratory instrumentation or machine learning approaches for signal processing will be advantageous, though the project will include training and development tailored to the student’s research activities.

Collaborative skills and effective communication are highly valued for interdisciplinary engagement within the project and research community.

This studentship includes a basic UKRI‑aligned stipend (tax‑free living allowance) per year and may offer opportunities for industrial sponsorship
, subject to funding conditions. Tuition fees for eligible UK students will be covered; international fee support will be considered in line with University and funding policies.

The closing date for applications is 1 April 2026
.