At a Glance
- Tasks: Explore innovative editing methods for large language models and test on factual benchmarks.
- Company: University of East Anglia, a leading institution in research and education.
- Benefits: Receive a competitive stipend of £21,805 annually for three years.
- Other info: Full-time study in Norwich with excellent academic support.
- Why this job: Contribute to groundbreaking research in AI and make a real impact in the field.
- Qualifications: Open to UK applicants with a passion for AI and research.
The predicted salary is between 21805 - 21805 £ per year.
University of East Anglia invites applications for a Ph D project on reliable, localised knowledge updating in large language models.
You will explore editing methods like ROME and MEMIT, compare with RAG and retrieval-augmented memory, and test on factual benchmarks.
The project is funded for three years, with a standard UK stipend of £21,805 annually, available to UK applicants, and begins on 1 October 2027.
Full-time study in Norwich is expected.
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PhD: Reliable Knowledge Editing for Large Language Models in Norwich employer: UAG
Queen Mary University of London is an exceptional employer, offering a vibrant work culture that fosters academic excellence and innovation. With opportunities for professional development and the unique experience of teaching in both London and Hainan, China, employees are encouraged to grow their skills while making a meaningful impact on students' academic journeys.
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We think this is how you could land PhD: Reliable Knowledge Editing for Large Language Models in Norwich
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We think you need these skills to ace PhD: Reliable Knowledge Editing for Large Language Models in Norwich
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
