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PhD studentship in Neuro-Symbolic AI - Correct Reasoning in Large Language Models

The University of Edinburgh

Qualification Type: PhD
Location: Edinburgh
Funding for: UK Students
Funding amount: £19,237
Hours: Full Time
Placed On: 9th January 2025
Closes: 15th February 2025

Deadline: 15 February 2025

One fully funded, full-time PhD position to work with Vaishak Belle in the School of Informatics, University of Edinburgh. The University of Edinburgh offers an exciting interdisciplinary, collaborative environment integrating different subfields of computer science and artificial intelligence. The appointed student will work in the Belle Lab, as part the Artificial Intelligence and its Applications Institute. The position is fully funded.

The aim of this project is to work on improving the reasoning capabilities and correctness of large language models through neuro-symbolic AI approaches. The research will focus on developing novel methods to enhance the logical reasoning and reliability of these models, combining symbolic reasoning with deep learning architectures.

Candidate's profile

Essential

  • MSc (or equivalent) in Computer Science, Artificial Intelligence or a related discipline (e.g., Math, Statistics, Logic)
  • Ability to communicate information clearly, orally and in writing, in English
  • A research statement (as discussed on the postgraduate degree link above — to understand relevance, the research statement may link to one of our papers or a closely related one and develops an independent idea while building on the expertise of the applicant)
  • A sample research paper — if a brief paper demonstrating any prior experience could be attached, or if applicable, one that has been published

Desirable

  • Experience (educational or research) with one or more of: large language models, computational logic, neuro-symbolic AI, formal verification, machine reasoning
  • If you have papers at conferences, workshops, symposia, or other informal or formal events, please explicitly mention this in your cover letter and CV, and include a link/attachment to the paper

More information about the lab: vaishakbelle.com/lab

Studentship and eligibility

The funded studentship starting in the academic year 2024/25 covers:

  • Full time PhD tuition fees for a student with a Home fee status (£4,786 per annum)
  • A tax-free stipend of GBP £19,237* per year for 3.5 years
  • Additional programme costs of £1,000 per year

Application information

Applicants should apply via the University’s admissions portal (EUCLID) and apply for the following programme: postgraduate.degrees.ed.ac.uk/index.php?r=site/view&edition=2024&id=494 with a start date of 01/05/2025 (Home applicants only)

Applicants should state “Neuro-symbolic AI funded position; Ref: Vaishak Belle’ in their application and Research Proposal document.

Complete applications submitted by 15th February 2025 will receive full consideration; after that date applications will be considered until the position is filled. The anticipated start date is 01/05/2025 but later start dates might need to be considered for international applicants needing to complete immigration processes prior to commencing studies.

Applicants must submit:

  • All degree transcripts and certificates (and certified translations if applicable)
  • Evidence of English Language capability (where applicable)
  • A short research proposal (max 2 pages)
  • A full CV and cover letter describing your background, suitability for the PhD, and research interests (max 2 pages)
  • Two references (note that it the applicant’s responsibility to ensure reference letters are received before the deadline)

Only complete applications (i.e., those that are not missing the above documentation) will progress forward to Academic Selectors for further consideration.

Environment

As a world-leading research-intensive University, we are here to address tomorrow’s greatest challenges. Between now and 2030 we will do that with a values-led approach to teaching, research and innovation, and through the strength of our relationships, both locally and globally.

www.ed.ac.uk/schools-departments/informatics

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