Postdoctoral Research Associate Grade 7

The project¿s key aim is to establish an innovative, robust, unified, and responsible AI framework that can be applied to both personalised text summarisation and deepfake detection, thereby facilitating the creation of potent solutions for precise text-based summarisation and discerning AI-generated content authenticity. Moreover, the proposal aims to construct a demonstration website to provide the public with access to personalised content summarisation and content authenticity verification services.

The project will be based on the Large Language Models (LLM) and the state-of-the-art diffusion-based generation model to generate some fake images, and we aim to distinguish the fake and real images through spectral and frequency domain. Based on the developed algorithms, we will construct a public website to verify the effectiveness of the framework.

You will have a PhD in a relevant computer science and engineering discipline (e.g., Computer Vision, Artificial Intelligence, etc.).

This post is available on a fixed term basis for 12 months, although an extension may be available.

Any applicants who are still awaiting their PhD to be awarded should be aware that if successful, they will be appointed at grade 6, spine point 30.  Upon written confirmation that they have been successful in being awarded their PhD, they will be moved onto grade 7, spine point 31 from the date of their award. 

The University has the right to close the vacancy early if it is deemed that there have been enough applications received.