Resilient AI Systems for Polar Glacier Monitoring

AI has become a valuable asset in day-to-day life. It has also become an invaluable part of any research. It is often associated and combined within autonomous systems for monitoring environmental changes. However, the trustworthiness of such systems still needs to undergo rigorous investigations. As the range and impact of such systems increase due to fast advances in their underlying technology, UKRI has funded a number of investigatory research “nodes” to address the trustworthiness of autonomous systems.

https://www.ukri.org/news/new-trustworthy-autonomous-systems-projects-launched/

The research node led by the University of York focuses on the resilience of such systems. An important aspect of resilience is to provide assurance that AI and autonomous systems can and will achieve their goals despite the uncertainty and disruption encountered in real-world environments.

This exciting PhD studentship opportunity will contribute to the Resilience Node’s research by exploring how AI/ML systems can be used in glacier environmental monitoring and how they can support autonomous missions in hard to access areas. The project will be aimed at devising fast methods for analysing (RGB, IR and multispectral) image-based and point cloud data, and sampled fiord water, to detect and track changes in glacier environments. It will also lay a foundation for devising low-energy autonomous systems capable of providing continuous observations of such environments. These systems will have to operate resiliently by taking into account their harsh environment, equipment limitations, lack of instant communication, and need for multi-signal processing.

The PhD student will have the unique opportunity to collaborate with a multidisciplinary team from Computer Science and collaborators from institutions pre-forming data acquisition in Polar Regions, including one of the Polar Stations in Svalbard. The studentship is designed to offer exceptional access to resources, training and career development and networking opportunities. Candidates are invited to familiarise themselves with the aims of the Resilience node https://resilience.tas.ac.uk

The successful candidate will conduct their research under the supervision of Professor Radu Calinescu at the University of York.

Apply for this Studentship:

We are seeking a highly motivated candidate who should have, or expects to be awarded, a first-class or 2.1 degree or a master’s degree in Computer Science or any other relevant discipline – or equivalent experience. Preferred skills include writing, communication, presentation and organization skills. The studentship is open to students holding Home fee status.

To be considered, you must apply online to a full-time on campus PhD in Computer Science at the University of York.

https://www.york.ac.uk/study/postgraduate/courses/apply?course=DRPCOMSSCI3

and quote the title of this project – Resilient AI Systems for Polar Glacier Monitoring - in your application.

Please also include the following in your application:

● A short research proposal (<1,500 words).

● A statement of purpose explaining how your competencies and previous

experiences makes you an appropriate candidate for this position.