EPSRC iCASE Studentship: Join a prestigious EPSRC-funded PhD opportunity at the University of Hull, in collaboration with QinetiQ, focusing on assuring Large Language Models (LLMs) through Neuro-Symbolic AI. This project aims to enhance LLM performance and trustworthiness by integrating Knowledge Graphs, addressing challenges in detecting inaccuracies and improving model quality.
EPSRC iCASE Studentship on Assuring Large Language Models Through Knowledge Graph Infusion
- 📅 Application Deadline: March 20, 2024
- 🤖 About the Project:
- QinetiQ is developing an AI Assurance Framework for responsible use of Large Language Models (LLMs) in the UK Defence and government agencies.
- Aiming to assure LLM products and enhance performance using Neuro-Symbolic AI, combining neural networks with symbolic systems like Knowledge Graphs.
- Focus on detecting hallucinations, falsehoods, contradictions, and knowledge gaps in LLM outputs over five stages.
- PhD project within the Responsible Artificial Intelligence Group at the University of Hull, renowned for Neuro-Symbolic AI research.
- Prestigious EPSRC iCASE studentship co-funded by Naimuri (A QinetiQ subsidiary).
- 🎓 PhD Student Responsibilities:
- Actively participate in the program, demonstrate good time management and organization.
- Work on and develop research questions, attend meetings, review literature, and complete tasks for PhD completion.
- Benefit from the Postgraduate Training Scheme at the University of Hull, enhancing research, professional, and personal skills.
- 📚 Research Training:
- Undertake the Postgraduate Training Scheme alongside the main degree.
- Gain an additional Certificate or Diploma in Research Training.
- 📝 How to Apply:
- Submit a personal statement.
- Include motivations for pursuing a PhD, interest in the project, skills matching requirements, and the wider significance of research.
- 💰 Funding:
- Prestigious EPSRC iCASE studentship co-funded by Naimuri, covering UK PhD tuition fees and a tax-free stipend (* £18,622 in 2023/24) for 4 years.
- Requires passing a Baseline Personnel Security Standard (BPSS) check.
- Full-time study only.
- 📜 Entry Requirements:
- Applicants should hold a minimum of a 2:1 degree in a Computer Science-related subject.
- Prior experience in ML/AI is desirable, and a taught MSc or master’s by Research in a relevant field is advantageous.
- This scholarship is available for full-time study only.
Designation: PhD Student
Research Area: Neuro-Symbolic AI, Large Language Models
Location: University of Hull, UK
Funding: Funded PhD (EPSRC iCASE Studentship)
Duration: 4 years
Application Deadline: March 20, 2024
| Qualification | Eligibility |
|---|---|
| Bachelor’s or Master’s degree in Computer Science or related field. | UK/EU nationality or settled status. |
| Strong programming skills (Python, TensorFlow, PyTorch). | Background in AI, Machine Learning, or Natural Language Processing. |
| Excellent academic record. | Ability to work independently and in a team. |
Job Description:
- Conduct research in the field of Neuro-Symbolic AI to assure and enhance Large Language Models.
- Collaborate with the Responsible Artificial Intelligence Group at the University of Hull and industry partners.
- Develop and implement methodologies using Knowledge Graphs to detect inaccuracies in LLM outputs.
- Contribute to the improvement of LLM inference, training, and architecture.
- Participate in academic activities, including attending meetings, literature reviews, and thesis writing.
How to Apply:
Interested candidates should submit the following documents:
- Personal statement addressing:
- Motivation for pursuing PhD study.
- Interest in the project.
- Relevance of skillset and any additional training needed.
- Wider significance of research in the area and potential future directions.
- Curriculum Vitae (CV) detailing academic and professional experience.
- Academic transcripts and certificates.
- Two academic references.
Last Date for Apply: March 20, 2024
Disclaimer: This job post is adapted from reliable sources. For further details and to apply, please refer to the official website. Check the official site for the most accurate and up-to-date information regarding eligibility criteria, application process, and deadlines.
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Supervisors:
- Professor Dhaval Thakker
- Dr. Koorosh Aslansefat
- Dr. Kevin Pimbblet
About Postgraduate Research at Hull:
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