PhD in Electromagnetic Sensing for Smart Manufacturing

RFCSR; Bristol; On-site; GBP 17,000 - 20,000; Full time

Benefits offered by this job

UKRI stipend

Fees covered for UK students

Job summary

The University of Bristol invites applications for a fully funded PhD studentship focused on advancing electromagnetic sensing technologies tailored for intelligent manufacturing systems and the development and characterisation of advanced materials.

The successful candidate will undertake original research combining experimental design, modelling and validation of EM sensing methods within a multidisciplinary engineering context, with access to world-class facilities and collaborations across

Qualifications

• Upper second-class honours degree (2:1) or equivalent in physics, electrical/electronic engineering, materials science, or a related field.
• International candidates are eligible to apply; funding terms depend on residency status and programme regulations.
• Strong interest in research and demonstrated academic excellence are essential.

Responsibilities

• Undertake original research combining experimental design, modelling and validation of EM sensing methods.
• Collaborate across multidisciplinary teams within engineering and with industry partners.
• Develop and apply data analysis and modelling techniques to characterise sensing performance.

Skills

Electromagnetic sensing

Sensor design

Materials characterisation

Experimental methods

Computational research methods

MATLAB

Python

Machine learning for signal processing

Education

Upper second-class honours degree (2:1) or equivalent

Tools

Electromagnetic simulation tools

Laboratory instrumentation

Job description

The University of Bristol invites applications for a fully funded PhD studentship focused on advancing electromagnetic sensing technologies tailored for intelligent manufacturing systems and the development and characterisation of advanced materials.

The successful candidate will undertake original research combining experimental design, modelling and validation of EM sensing methods within a multidisciplinary engineering context, with access to world-class facilities and collaborations across