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University of York, Department of Computer Science PhD Projects, Programmes & Scholarships
We have 15 University of York, Department of Computer Science PhD Projects, Programmes & Scholarships
We have 15 University of York, Department of Computer Science PhD Projects, Programmes & Scholarships
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Situational Awareness for Resilient Autonomous Systems
The project. Autonomous systems are an increasing part of the infrastructure of daily life. As the range and importance of such systems increases as the underlying technology rapidly develops, the UKRI has funded a range of investigatory research “nodes” to address the trustworthiness of autonomous systems. Read more
Uncertainty Mitigation for Resilient Autonomous Systems
The Project. Autonomous systems are an increasing part of the infrastructure of daily life. As the range and importance of such systems increases and the underlying technology rapidly develops, the UKRI has funded a range of investigatory research “nodes” to address the trustworthiness of autonomous systems. Read more
Defeasible Reasoning for Resilient Autonomous Systems
The project. Autonomous systems are an increasing part of the infrastructure of daily life. As the range and importance of such systems increases as the underlying technology rapidly develops, the UKRI has funded a range of investigatory research “nodes” to address the trustworthiness of autonomous systems. Read more
Dynamic Assurance for Resilient Autonomous Systems
The project. Autonomous systems are an increasing part of the infrastructure of daily life. As the range and importance of such systems increases as the underlying technology rapidly develops, the UKRI has funded a range of investigatory research “nodes” to address the trustworthiness of autonomous systems. Read more
Evaluation of ML/AI techniques to increase resilience of IoT Edge networks under cyberattacks
About the project. Cyber Security is one of the key challenges and a well known issue in the IoT ecosystem. Due to heterogeneity and resource constraints, optimisation, testing and validation of the end-to-end systems is a hard problem which leads to unsecure systems. Read more
Reconfigurable Architectures for Scientific Computing
Supercomputers play an important role in the field of computational science, and are used for a wide range of computationally intensive tasks in various fields across the engineering and sciences spectrum [1]. Read more
Solver Feedback Loops for Automated Constraint Modelling
Constraint satisfaction and optimization problems are an important class of problems in artificial intelligence, where a set of decisions need to be made together, so that some requirements are satisfied and perhaps also optimizing some criteria. Read more
How Do Real-World Engineers Understand Hazards and Develop Safety Requirements for Autonomous Systems?
There is a lot of activity in developing new methods for doing hazard analysis for autonomous systems (e.g. [1,2]). All of this is, inherently, an attempt to change engineering practice — every AS developer organisation is already doing something in this space, and we are implicitly trying to change that for the better. Read more
How Does Safety-Critical Software Actually Get Developed?
We have lots of ideas, and in particular assumptions, about how safety-critical software is developed, but there is very little public knowledge of an ethnographic, descriptive character. Read more
Software Safety Cases In the Wild
Software safety cases — rigorous structured arguments that some given safety-critical software system is safe enough to operate — are widely used. Read more
Artificial Systems Teaching Each Other
Deep learning relies on training by using huge amounts of data. However, there are many applications where such data are not available due to various reasons, not least because of privacy concerns. Read more
Graphs of Deep Networks
This project aims to develop a new approach for joint syntactical and statistical data representation modelling. Read more
Video Transformers
The aims of this project are to develop new methods for processing videos, leading to applications such as video classification, human activity recognition or video generation [1]. Read more
Mixtures of Generative Deep Learning Networks
The main generative deep learning models are the Variational Autoencoders (VAE) [1] or Generative adversarial networks (GANs) [2]. Read more
Research opportunities in Computer Science
Our Department of Computer Science has a strong international reputation for conducting research that has real impact, tackles fundamental questions and addresses interdisciplinary problems which face today's computer scientists. Read more
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