Reinforcement learning for manipulating the electromagnetic environment in defence scenarios

We are seeking a highly motivated and talented individual to join our Electromagnetic Environment (EME) Hub as a PhD researcher. The project will focus on developing reinforcement learning techniques to control the transmit chain to achieve desired effects in a dynamic and contested defence scenario, for example, to degrade an adversary’s wireless communications capability.

The successful candidate will be responsible for developing and implementing reinforcement learning algorithms. These will optimize the RF transmit chain block parameters, such as gain, frequency, modulation, subsystem matching etc so that multiple waveforms can be delivered to specific targets with minimal interference to surrounding systems.

The project will involve designing and implementing experiments to evaluate the performance of the proposed approach and compare it with traditional optimization techniques. Identification of advantages and disadvantages and lessons learned during the research would be necessary research outputs.

The ideal candidate should have experience in signal processing, machine learning, and wireless communication systems. Experience with reinforcement learning techniques and programming languages such as Python or Matlab is highly desirable. Specifically, Python libraries (RLlib) and knowledge of Linux operating system would be advantageous.

The position starts in October 2023 and is fully funded by Defence Science Technology Laboratory (Dstl) for three years. The successful candidate will have the opportunity to work with leading researchers in the field, present their work at international conferences, and publish in high-impact journals. Furthermore, there will be opportunities to attend summer schools and Continuing Professional Development courses.

The EME Hub is a consortium of five leading UK universities, so, the candidate will join a vibrant research community. As this position is sponsored by Dstl, with associated security implications, this PhD position is only open to UK nationals.

To apply, please submit your CV, a cover letter, and contact details of two referees. Don't hesitate to contact the primary supervisor, Dr Kostas Kyriakopoulos, for more details and to raise your interest.

Supervisors

Primary supervisor: Kostas Kyriakopoulos

Secondary supervisors: Chinthana Panagamuwa & James Flint

Entry requirements for United Kingdom

The successful applicant should hold or expect to achieve a 1st class or high 2:1 honours (or equivalent) degree in electronic/electrical engineering, computer science or a closely related discipline. An MSc with Distinction is desirable. Strong research abilities with appropriate coding skills are required.

Knowledge of radio frequency fundamentals and experience with machine learning techniques, Python, and Linux are desirable. The successful candidate is also expected to be an enthusiastic team player who can work both independently and communicate effectively with others.

English language requirements

Applicants must meet the minimum English language requirements. Further details are available on the International website.

How to apply

All applications should be made online. Under programme name, select ‘Electronic, Electrical and Systems Engineering’  and quote the advert reference number FP-KK-2023.

Please submit a CV and the minimum supporting documents by the advert closing date. Failure to do so will mean that your application cannot be taken forward for consideration.  See studentship assessment criteria.

Apply now