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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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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