PhD Studentship: Robustness Analysis and Safety Verification of AI-Based Multiagent Systems: Healthcare Applications

Applications are invited for a PhD studentship in the Department of Engineering. The successful candidate will have the opportunity to work on analysis of the performance/robustness s for AI-Based Multiagent Systems: Healthcare Applications.

This PhD project aims to improve the robustness and safety of AI-driven multiagent systems in healthcare. The main objective is to develop methods and tools that ensure the reliable and safe operation of these systems in medical environments. Key tasks include examining interactions between AI agents and their surroundings, while ensuring their collective behaviour complies with strict safety standards. Challenges addressed involve maintaining consistent performance across varied conditions, managing unexpected agent interactions, and preventing system failures. The project targets two main applications: first, employing multi-robot systems to assist elderly and disabled individuals in care facilities and homes with tasks such as medication reminders and emergency alerts. Second, using these systems during pandemics for temperature screening, patient triage, and delivering essentials to isolated patients, thereby reducing human contact and virus transmission.

Eligibility and requirements 

The candidate should possess a first-class or upper second-class BEng/MEng degree (or equivalent or higher) in Automatic Control, Applied Mathematics or a related field. They should also demonstrate an aptitude for original research.

Scholarship: e.g. The studentship is for 3 years and will provide an annual tax-free stipend that tracks the UKRI rate (Actually £21,237 p/a) and tuition fees.

Optional: Additional income: Each student may also have the opportunity to earn around £2,200/year on an average (max. is around £4,300/year) through a teaching assistantship.

In addition, project/consumable costs of £1500 are provided.

The candidate should possess a good understanding of Control Theory and AI algorithms including Deep Reinforcement Learning. A candidate who demonstrates exceptional aptitude in one or more of these areas (as evidenced, for instance, through strong academic credentials or research papers in reputable, peer-reviewed journals/conferences) may be accorded preference. Ideally, the successful candidate should have proven skills in Robustness Analysis of Multiagent Systems. 

A doctoral candidate is expected to meet the following pre-requisites for their PhD: 

• Demonstrate a sound knowledge of their research area;
• Achieve and demonstrate significant depth in at least a few chosen sub-areas relevant to their primary research area;
• Demonstrate the ability to conduct independent research, including a critical assessment of their own and others’ research;

If you are interested in applying, please address any initial informal enquiries by email to:

Dr. Abdelhafid Zenati abdelhafid.zenati@city.ac.uk and/or

Prof. Nabil Aouf nabil.aouf@city.ac.uk

How to apply

Online applications should be submitted via the PhD/MPhil Electrical and Electronic Engineering course page

For queries regarding the application process, please contact pgr.sst.enquire@city.ac.uk

City, University of London is committed to promoting equality, diversity and inclusion in all its activities, processes, and culture for our whole community, including staff, students and visitors.

We welcome applications regardless of age, caring responsibilities, disability, gender identity, gender reassignment, marital status, nationality, pregnancy, race and ethnic origin, religion and belief, sex, sexual orientation and socio-economic background. City operates a guaranteed interview scheme for disabled applicants.

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