Fully Funded and QinetiQ PhD Scholarship: Explainable Artificial Intelligence for Automated Knowledge Discovery and Scientific Trend Prediction - Swansea, United Kingdom - Swansea University

Description

Funding providers: Swansea University's Faculty of Science and Engineering, and QinetiQ

Subject areas: Artificial Intelligence, Computer Science

Project start date:

• 1^st July 2024 (Enrolment open from mid-June)

Project description:

The number of scientific papers published is increasing rapidly every year. The overwhelming volume of the literature makes it challenging to keep up with the latest research and developments. Working closely with the project partner QinetiQ, this project will combine state-of-the-art machine learning methods, natural language models and image recognition to develop a human-in-the-loop system for systematic reviews and predictive analytics. We envisage that the system will be able to collate and analyse a significant amount of research publications. Furthermore, we expect the system to quantify and extrapolate research trends that may have significant impacts on technology development. Our key objectives are:

• Optimise an automated systematic review system that integrates texts, figures and tables from scientific publications and other credible sources;
• Develop and validate deep neural network models that predict scientific trends and their impacts;
• Deliver an integrated interface that renders model outputs with explainability, transparency and efficiency.

The project partner, QinetiQ, is a multinational FTSE 250 company with a global workforce exceeding 6000 employees. It offers world-class expertise in advice, services, and innovative technology-based products in the manufacturing, security, defence, finance, energy, and telecom sectors. This collaborative research initiative signifies QinetiQ's commitment to informed investment in AI and advanced computing. The overarching goal is to pioneer leading-edge solutions, particularly in the domains of application-specific analytics and data science. Through this joint effort, QinetiQ aims to push the boundaries of innovation, ensuring they remain at the forefront of technological advancements in these emerging and critical areas.

Eligibility

Candidates must hold an undergraduate degree at 2.1 level in Computer Science, Mathematics or a closely related discipline, or an appropriate master's degree with a minimum overall grade at 'Merit' (or Non-UK equivalent as defined by Swansea University). If you are eligible to apply for the scholarship (i.e. a student who is eligible to pay the UK rate of tuition fees) but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency.

Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.

£18,622. This scholarship covers the full cost of tuition fees and an annual stipend at UKRI rate (currently £18,622 for 2023/24). Additional research expenses will also be available.