Qualification Type: | PhD |
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Location: | Kingston upon Hull |
Funding for: | UK Students |
Funding amount: | The studentship covers UK PhD tuition fees and a tax-free stipend of the current UKRI rate (£18,622 in 2023/24) for 4 years. |
Hours: | Full Time |
Placed On: | 16th February 2024 |
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Closes: | 31st March 2024 |
Recently, Large Language Models (LLMs) have seen huge advancement. QinetiQ is developing an AI Assurance Framework, to allow such tools to be responsibly utilised by UK Defence and other government agencies. This project aims to assure LLM products and improve their performance using Neuro-Symbolic AI (NAI). Cutting edge research in NAI focuses on combining neural network-based technologies with symbolic systems like Knowledge Graphs. Over five stages, we will explore how to use knowledge graphs to detect hallucinations, falsehoods, contradictions, and knowledge gaps in LLM outputs. Through this, we aim to establish robust mechanisms for LLM assurance and improvement.
This PhD in Computer Science project sits within the Responsible Artificial Intelligence Group at the University of Hull. The group is renowned for its work on NAI. As a PhD student, you will join a growing research community in this field. This is a prestigious EPSRC (Engineering and Physical Sciences Research Council) iCASE studentship co-funded by Naimuri (A QinetiQ subsidiary).
As a PhD student, you will be expected to actively participate within the programme of study, showing good time management and organisation. You are expected to work upon and further develop initial research questions, completing tasks required to gain a PhD such as attending meetings, regularly reviewing literature, completing pertinent studies, disseminating their work at appropriate forums and writing a thesis on the topic.
You will benefit from the Postgraduate Training Scheme (PGTS) at the University of Hull (UoH), an accredited training program designed for PhD students. You will receive all necessary resources (including a desk, computer, and cloud-computing access) and training (academic supervision, modules, conferences, seminars, and workshops as applicable). Additionally, QinetiQ will provide industrial supervision for the project.
For informal enquires please contact:
Please contact the project lead: Professor Dhaval Thakker (D.Thakker@hull.ac.uk)
Start date 27th May 2024
Supervisors:
The principal supervisor of the project will be Professor Dhaval Thakker, with co-supervisors Dr Koorosh Aslansefat, and Dr Kevin Pimbblet from the University of Hull, with supervision team members from Naimuri (Dr Rowan Morris, Dr James Ramsden).
Funding:
This is a prestigious EPSRC iCASE studentship co-funded by Naimuri (A QinetiQ subsidiary). The studentship covers UK PhD tuition fees and a tax-free stipend of the current UKRI rate (£18,622 in 2023/24) for 4 years.
Eligibility Requirements:
Applicants should hold a minimum of a 2:1 degree in a Computer Science-related subject. Possessing a taught MSc or master’s by Research in a relevant field would be advantageous. For more details on our entry requirements please visit the postgraduate admissions webpage.
To be accepted onto this opportunity requires the student/researcher to pass a Baseline Personnel Security Standard (BPSS) check.
This scholarship is available only for full-time Home study.
How to Apply:
You will need to supply a personal statement when applying for this scholarship position. Find out more about writing a personal statement. APPLY HERE For Full Time PhD Scholarship Closing Date: 31st March 2024
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