Supervisor: Prof. Yang Hao
Project Description
This project aims to develop foundational insights into the application of perovskite materials in the fields of electromagnetics, THz, and wireless communications. The research will explore how automated high-throughput experimentation and machine learning can accelerate material discovery and optimisation, focusing on perovskites with tunable electromagnetic properties. The findings will inform the development of advanced devices and systems for next-generation wireless communications and high-frequency applications. Relevant previous studies can be found at https://www.nature.com/articles/s41467-024-50884-y.
PhD topics for this position could explore any combination of the following areas:
- Tunable Electromagnetic Devices: Investigating perovskite-based materials for designing tunable components such as antennas, filters, and metamaterials. This research could involve exploring how automated synthesis and characterization can create materials with dynamic dielectric properties, enabling adaptive electromagnetic devices.
- THz Waveguides and Signal Modulators: Developing perovskite materials optimized for THz applications, including low-loss waveguides and efficient signal modulators. This research will focus on leveraging high-throughput methods to identify materials that enhance signal integrity in THz communication systems.
- Microwave and RF Circuit Materials: Using high-throughput experimentation to discover perovskite compositions with low dielectric losses and high permittivity. The goal is to enhance the performance of microwave and RF circuits, contributing to improved wireless communication technologies.
- Data-Driven Electromagnetic Material Design: Leveraging machine learning techniques to predict and optimise the properties of perovskite materials based on experimental data. This project will integrate high-throughput experimentation data with predictive modelling to accelerate the discovery of high-performance materials for electromagnetic applications.
Prerequisites:
- A Master’s degree (Distinction or equivalent) or an expected completion of such qualifications before starting the PhD.
- A strong interest in robotics, automation, and self-driving laboratory technologies.
- Proficiency in control systems design and implementation.
- Familiarity with embedded electronics, including sensor integration and microcontroller programming.
- Experience with robotics frameworks (e.g., ROS) or automation tools.
- Solid programming skills in Python, C++, or similar languages, with an emphasis on software development for real-time systems.
- A passion for creating innovative, autonomous systems to accelerate scientific discovery.
The PhD studentship is funded by EPSRC Doctoral Landscape Award open to those with Home and International fee status. However, the number of students with international fee status who can be
recruited is capped according to the EPSRC terms and conditions, so competition for international places is particularly strong. The PhD student will receive an annual stipend of £21,237 for the academic year 2024/25, with funding available for a duration of up to 3.5 years.
How to apply
Queen Mary is interested in developing the next generation of outstanding researchers and decided to invest in specific research areas.
Applicants should work with their prospective supervisor and submit their application following the instructions at: http://eecs.qmul.ac.uk/phd/how-to-apply/.
The application should include the following:
- CV (max 2 pages)
- Cover letter (max 4,500 characters) stating clearly in the first page whether you are eligible for a scholarship as a UK resident (https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/eligibility)
- Research proposal (max 500 words)
- 2 References
- Certificate of English Language (for students whose first language is not English)
- Other Certificates
Please note that to qualify as a home student for the scholarships, a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years before the start of the studentship. For more information please click here.
Application Deadline
The deadline for applications is the 29th of January 2025.
For general enquiries contact Mrs. Melissa Yeo (administrative enquiries) or Dr. Arkaitz Zubiaga (academic enquiries) with the subject “EECS 2025 PhD scholarships enquiry”.
For specific enquiries contact Prof Yang Hao.