Introduction
Are you passionate about advancing the frontiers of Large Language Models (LLMs) and ensuring their responsible use in critical sectors like UK Defence and government agencies? Join the prestigious EPSRC iCASE studentship at the University of Hull’s Responsible Artificial Intelligence Group, working in collaboration with QinetiQ’s AI Assurance Framework.
About the Project
- AI Assurance Framework: QinetiQ is pioneering the development of an AI Assurance Framework, ensuring responsible utilization of LLMs in critical sectors like UK Defence and government agencies.
- Neuro-Symbolic AI: Dive into the evolving field of Neuro-Symbolic AI, combining neural network-based technologies with symbolic systems like Knowledge Graphs.
- Project Objectives: Explore the use of knowledge graphs to detect hallucinations, falsehoods, contradictions, and knowledge gaps in LLM outputs. Enhance LLM inference, training, and architecture to establish robust mechanisms for LLM assurance and improvement.
Why Choose this PhD?
- Responsible AI Group: Join the renowned Responsible Artificial Intelligence Group at the University of Hull, consisting of 7 staff members and over 10 PhD students focused on Neuro-Symbolic AI.
- EPSRC iCASE Studentship: This prestigious Engineering and Physical Sciences Research Council studentship is co-funded by Naimuri, a QinetiQ subsidiary.
- Industry Collaboration: Benefit from industrial supervision provided by QinetiQ and Naimuri, ensuring a seamless blend of academic and practical expertise.
- Financial Support: Receive full coverage of UK PhD tuition fees and a tax-free stipend at the current UKRI rate (£18,622 in 2023/24) for 4 years, ensuring financial stability throughout your academic pursuit.
- Security Clearance: As a requirement, successfully pass a Baseline Personnel Security Standard (BPSS) check, enhancing your profile for impactful roles in the defense and government sectors.
What You Gain
- Postgraduate Training Scheme: Access an accredited training program designed to enhance your research, professional, and personal skills.
- Comprehensive Resources: Receive all necessary resources, including a dedicated desk, computer, and cloud-computing access.
- Structured Training: Engage in academic supervision, modules, conferences, seminars, and workshops to ensure a well-rounded learning experience.
Program Details:
- Full-Time Study: Immerse yourself in a comprehensive learning experience with this full-time scholarship, allowing you to dedicate your efforts to groundbreaking research.
- Thesis Submission: Complete your journey by submitting your final thesis within 48 months, showcasing the depth of your contributions to the field.
- Educational Background: Hold a minimum of a 2:1 degree in a Computer Science-related subject, providing a solid foundation for advanced research.
- ML/AI Experience: While not mandatory, prior experience in Machine Learning (ML) or Artificial Intelligence (AI) through education or work is desirable, enhancing your ability to contribute meaningfully.
- Advantageous Qualifications: Possession of a taught MSc or master’s by Research in a relevant field would be advantageous, demonstrating your commitment to specialized knowledge.
Important Dates
- Application Deadline: March 20, 2024
- Start Date: May 2024
How to Apply
Craft a compelling personal statement addressing:
- Your motivation for pursuing a PhD.
- Why this project excites you.
- How your skills align with project requirements and any additional training needs.
- The broader significance of research in this area and potential future research directions.
Apply for the Scholarship: Click here to start your journey!
For informal inquiries, contact the project lead: Professor Dhaval Thakker. Join the Future of AI Research – Apply Now for the QinetiQ EPSRC iCASE Studentship at the University of Hull – Apply Now!
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This article is prepared by Rabiul Alam, a core member of our StudyAbroad.ac team.
