Job Description
Be Part of Research That Shapes the Future of AI
At the University of Edinburgh, careers are built around curiosity, collaboration, and real-world impact. Whether in research, teaching, or professional services, our community is united by a shared ambition: to push boundaries and contribute meaningfully to society.
We are now inviting applications for a Post-Doctoral Research Associate (PDRA) to join the School of Informatics for an 18-month research project focused on benchmarking sparse, reasoning, and agentic foundation models.
This position offers the chance to work at the forefront of AI systems research within one of Europe’s leading AI research environments.
The Research Project
This role is funded by the UK’s Advanced Research and Invention Agency (ARIA) under its Scaling Compute: AI at 1/1000th the Cost programme (TA4 Benchmarking strand).
The £2 million project aims to develop next-generation AI benchmarks capable of measuring trade-offs between cost, performance, accuracy, and energy efficiency across rapidly evolving hardware ecosystems.
The broader goal is ambitious: enabling AI systems that are faster, greener, and significantly more cost-efficient.
Your Role in the Team
Working under the supervision of Dr Edoardo Ponti and Dr Luo Mai, you will:
- Conduct advanced research in efficient LLM and VLM architectures
- Design and implement benchmarking pipelines for foundation models
- Evaluate performance across diverse hardware platforms
- Contribute to collaborative work with partners at Imperial College and EPCC (one of the UK’s leading supercomputing centres)
- Publish findings and present at international conferences
- You will also benefit from funded international conference travel and access to high-performance computing (HPC) infrastructure.
What We’re Looking For
We’re seeking a researcher with intellectual curiosity and a collaborative mindset.
Essential Background
- PhD (completed or near completion) in NLP, Machine Learning, ML Systems, or a related discipline
- Evidence of research excellence (publications, preprints, or equivalent outputs)
- Experience training and deploying large-scale foundation models (LLMs/VLMs)
- Strong programming and experimental skills
- Familiarity with AI hardware performance and cost metrics
- While no single criterion is decisive, we aim to appoint candidates with the strongest overall research profile.
Working Environment & Flexibility
- This is a full-time (35 hours) position, though hybrid working arrangements may be considered (non-contractual).
- The University welcomes UK and international applicants. Visa sponsorship may be available in accordance with UK Skilled Worker visa regulations
- All candidates must demonstrate their right to work in the UK prior to appointment
Equality, Diversity & Inclusion
The University is committed to building an inclusive academic community. We hold a Silver Athena SWAN Award and are members of the Race Equality Charter and Stonewall Scotland Diversity Champions.
- Our policies align with the UK’s legal framework under the Equality Act 2010
- We actively encourage applications from candidates of all backgrounds.
- Salary, Benefits & Professional Support
- A role with us comes with more than a payslip.
What You Can Expect:
- Competitive salary at Grade UE07
- Generous annual leave allowance
- Defined benefits pension scheme
- Employee discounts and lifestyle benefits
- Professional development opportunities
- Access to cutting-edge research facilities
- A vibrant international academic community
- Pension arrangements follow the UK’s public sector pension framework
- We are also committed to responsible research and innovation, consistent with UKRI guidance
Application Process
To apply, please submit:
- A current CV
- A cover letter outlining research interests and suitability
- Up to three scientific papers demonstrating research quality and alignment with the project
- Â Application deadline: 5 March 2026 (11:59pm UK time)
Why Edinburgh?
The School of Informatics at the University of Edinburgh is internationally recognised for excellence in Artificial Intelligence, Machine Learning, and Natural Language Processing. Joining us means becoming part of a research culture that values collaboration, ambition, and responsible innovation.