PhD studentship: Assured and Scalable Self-Adaptation for the Engineering of Trustworthy Autonomous Robotic Teams

Applications are invited for a three-year PhD studentship, supported by the Defence Science & Technology Laboratory (DSTL), to be undertaken within the Department of Computer Science (http://www.cs.york.ac.uk/) at the University of York. The successful applicant will join one of UK’s top research departments in Computer Science, and will pursue research in the rapidly evolving areas of machine learning and formal methods for safety-critical systems, under the supervision of Dr. Simos Gerasimou and Dr. Javier Camara Moreno. The PhD project will include secondments at École Nationale Supérieure de Techniques Avancées, ParisTech in Paris, France, where the PhD student will be co-supervised by Dr Natalia Díaz Rodríguez.

Background of the Project

Robotic teams and other distributed autonomous systems (DAS) are increasingly used in several application domains including logistics, manufacturing, and infrastructure inspection. Assuring the trustworthiness of DAS carrying out a safety-critical task collaboratively is very challenging due to uncertainties and risks associated with the operating environment, team member failures, etc. To overcome these challenges, the distributed-control software of DAS should exhibit high levels of scalability and optimality underpinned by assurance evidence that the DAS operates safely in continually changing and unexpected scenarios. The PhD project will contribute significantly to addressing this challenge by leveraging the capabilities from both data-driven (using machine learning) and model-based (using formal methods) paradigms to devise assured and scalable self-adaptation techniques that support the development of trustworthy distributed-control software for DAS. These techniques will be integrated with state-of-the-art DAS middleware and their feasibility will be validated through a demonstrator both in simulation and using mobile robots available in our lab.

Research supervision

If successful, you will conduct your research under the co-supervision of:

Dr Simos Gerasimou - https://www-users.cs.york.ac.uk/simos/

Dr Javier Camara Moreno - https://www-users.york.ac.uk/~jcm567/index.shtml

Dr Natalia Díaz Rodríguez - https://nataliadiaz.github.io

To apply for this studentship

You must apply online for a full-time PhD in Computer Science (https://www.cs.york.ac.uk/postgraduate/research-degrees/phd/#tab-4)

You must state “ASSA DSTL Studentship” in the “Funding information” section of your application.

There is no need to write a formal research proposal in your application to study as this studentship is for a specific PhD project. However, a research statement elaborating your interest in the project and how your skills match the project requirements is desirable.

We will look favourably on applicants that can demonstrate a strong mathematical background, a keen interest in machine learning and AI, and excellent writing, communication, presentation and organization skills.

This project is being interviewed for and filled on a rolling basis. Please submit your application at your earliest opportunity.