PhD Studentship: Sub-THz Sensing for Dynamic Particulate Characterization
University of Birmingham
Fully Funded PhD Studentship (UK Students Only) Real-Time Sub-THz Electromagnetic Sensing and Machine Learning for Dynamic Particulate Characterization University of Birmingham with support from Rolls-Royce We are seeking an exceptionally motivated and enthusiastic student to undertake a fully funded PhD at the Microwave Integrated Systems Laboratory (MISL), University of Birmingham, with support from Rolls-Royce plc. This fully funded PhD project, with support from a leading industrial partner, will explore the...
Fully Funded PhD Studentship (UK Students Only) Real-Time Sub-THz Electromagnetic Sensing and Machine Learning for Dynamic Particulate Characterization University of Birmingham with support from Rolls-Royce We are seeking an exceptionally motivated and enthusiastic student to undertake a fully funded PhD at the Microwave Integrated Systems Laboratory (MISL), University of Birmingham, with support from Rolls-Royce plc. This fully funded PhD project, with support from a leading industrial partner, will explore the...
Opportunity details
Fully Funded PhD Studentship (UK Students Only) Real-Time Sub-THz Electromagnetic Sensing and Machine Learning for Dynamic Particulate Characterization University of Birmingham with support from Rolls-Royce We are seeking an exceptionally motivated and enthusiastic student to undertake a fully funded PhD at the Microwave Integrated Systems Laboratory (MISL), University of Birmingham, with support from Rolls-Royce plc. This fully funded PhD project, with support from a leading industrial partner, will explore the development of next-generation intelligent sensing and data analysis techniques for aerospace applications. The research aims to address a technological challenge with the potential to improve safety, reliability, and operational efficiency in future aerospace systems. The successful candidate will investigate novel sensing methodologies, develop physics-informed computational models, and apply state-of-the-art machine learning techniques to extract meaningful information from complex measurement data. The project combines fundamental research with practical engineering challenges, offering opportunities to contribute to technologies with real-world industrial impact. This project provides access to world-class experimental facilities, close collaboration with industry, and the opportunity to work on cutting-edge technologies that could shape the next generation of intelligent aerospace sensing systems. Applicant Requirements: We welcome applications from candidates who hold, or expect to obtain, a First-Class Honours degree (or equivalent) in Electronic Engineering, Electrical Engineering, Physics, Computer Science, or a closely related discipline. The ideal candidate will have: A strong background in radar, microwave engineering, signal processing, electrom...
Eligibility
The successful candidate will investigate novel sensing methodologies, develop physics-informed computational models, and apply state-of-the-art machine learning techniques to extract meaningful information from complex measurement data. Applicant Requirements: We welcome applications from candidates who hold, or expect to obtain, a First-Class Honours degree (or equivalent) in Electronic Engineering, Electrical Engineering, Physics, Computer Science, or a closely related discipline. The ideal candidate will have: A strong background in radar, microwave engineering, signal processing, electromagnetics, machine learning, or related areas. Experience with programming in Python and/or MATLAB.
Requirements
The successful candidate will investigate novel sensing methodologies, develop physics-informed computational models, and apply state-of-the-art machine learning techniques to extract meaningful information from complex measurement data. Applicant Requirements: We welcome applications from candidates who hold, or expect to obtain, a First-Class Honours degree (or equivalent) in Electronic Engineering, Electrical Engineering, Physics, Computer Science, or a closely related discipline. The ideal candidate will have: A strong background in radar, microwave engineering, signal processing, electromagnetics, machine learning, or related areas. Experience with programming in Python and/or MATLAB.
Funding and benefits
Funding eligibility: UK Students.
Required documents
CV
How to apply
To apply, please send: Your CV. A brief statement of interest outlining your research experience and motivation for applying. Applications should be sent to: Dr Fatemeh Norouzian – f.norouzian@bham.ac.uk Prof. Marina Gashinova – m.s.gashinova@bham.ac.uk
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Recorded source check: August 6, 2026. A stored check date does not guarantee that every field is complete or still current. Compare the provider, eligibility, funding and deadline with the live official call before applying.
Benefits
Funding eligibility: UK Students.
Eligibility summary
The successful candidate will investigate novel sensing methodologies, develop physics-informed computational models, and apply state-of-the-art machine learning techniques to extract meaningful information from complex measurement data. Applicant Requirements: We welcome applications from candidates who hold, or expect to obtain, a First-Class Honours degree (or equivalent) in Electronic Engineering, Electrical Engineering, Physics, Computer Science, or a closely related discipline. The ideal candidate will have: A strong background in radar, microwave engineering, signal processing, electromagnetics, machine learning, or related areas. Experience with programming in Python and/or MATLAB.
Requirements
The successful candidate will investigate novel sensing methodologies, develop physics-informed computational models, and apply state-of-the-art machine learning techniques to extract meaningful information from complex measurement data. Applicant Requirements: We welcome applications from candidates who hold, or expect to obtain, a First-Class Honours degree (or equivalent) in Electronic Engineering, Electrical Engineering, Physics, Computer Science, or a closely related discipline. The ideal candidate will have: A strong background in radar, microwave engineering, signal processing, electromagnetics, machine learning, or related areas. Experience with programming in Python and/or MATLAB.
Documents required
CV
Language/test requirements
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